scholarly journals Evaluation of Participant Success in Gamified Drone Training Simulator Using Brain Signals and Key Logs

2021 ◽  
Vol 11 (8) ◽  
pp. 1024
Author(s):  
Durmuş Koç ◽  
Ahmet Çağdaş Seçkin ◽  
Zümrüt Ecevit Satı

The risk of accidents while operating a drone is quite high. The most important solution is training for drone pilots. Drone pilot training can be done in both physical and virtual environments, but the probability of an accident is higher for pilot trainees, so the first method is to train in a virtual environment. The purpose of this study is to develop a new system to collect data on students' educational development performance of students during the use of Gamified Drone Training Simulator and objectively analyze students' development. A multimodal recording system that can collect simulator, keystroke, and brain activity data has been developed to analyze the cognitive and physical activities of participants trained in the gamified drone simulator. It was found that as the number of trials increased, participants became accustomed to the cognitive load of visual/auditory tasks and therefore the power in the alpha and beta bands decreased. It was observed that participants' meditation and attention scores increased with the number of repetitions of the educational game. It can be concluded that the number of repetitions lowers stress and anxiety levels, increases attention, and thus enhances game performance.

2000 ◽  
Author(s):  
Ralph Mager ◽  
R. Stoermer ◽  
A. Roessler ◽  
F. Mueller-Spahn ◽  
A. Bullinger

2016 ◽  
Vol 371 (1705) ◽  
pp. 20160278 ◽  
Author(s):  
Nikolaus Kriegeskorte ◽  
Jörn Diedrichsen

High-resolution functional imaging is providing increasingly rich measurements of brain activity in animals and humans. A major challenge is to leverage such data to gain insight into the brain's computational mechanisms. The first step is to define candidate brain-computational models (BCMs) that can perform the behavioural task in question. We would then like to infer which of the candidate BCMs best accounts for measured brain-activity data. Here we describe a method that complements each BCM by a measurement model (MM), which simulates the way the brain-activity measurements reflect neuronal activity (e.g. local averaging in functional magnetic resonance imaging (fMRI) voxels or sparse sampling in array recordings). The resulting generative model (BCM-MM) produces simulated measurements. To avoid having to fit the MM to predict each individual measurement channel of the brain-activity data, we compare the measured and predicted data at the level of summary statistics. We describe a novel particular implementation of this approach, called probabilistic representational similarity analysis (pRSA) with MMs, which uses representational dissimilarity matrices (RDMs) as the summary statistics. We validate this method by simulations of fMRI measurements (locally averaging voxels) based on a deep convolutional neural network for visual object recognition. Results indicate that the way the measurements sample the activity patterns strongly affects the apparent representational dissimilarities. However, modelling of the measurement process can account for these effects, and different BCMs remain distinguishable even under substantial noise. The pRSA method enables us to perform Bayesian inference on the set of BCMs and to recognize the data-generating model in each case. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’.


2012 ◽  
Vol 17 (1) ◽  
pp. 5-26
Author(s):  
Hans Goller

Neuroscientists keep telling us that the brain produces consciousness and consciousness does not survive brain death because it ceases when brain activity ceases. Research findings on near-death-experiences during cardiac arrest contradict this widely held conviction. They raise perplexing questions with regard to our current understanding of the relationship between consciousness and brain functions. Reports on veridical perceptions during out-of-body experiences suggest that consciousness may be experienced independently of a functioning brain and that self-consciousness may continue even after the termination of brain activity. Data on studies of near-death-experiences could be an incentive to develop alternative theories of the body-mind relation as seen in contemporary neuroscience.


2020 ◽  
Author(s):  
Nikhil Goyal ◽  
Dustin Moraczewski ◽  
Peter Bandettini ◽  
Emily S. Finn ◽  
Adam Thomas

AbstractUnderstanding brain functionality and predicting human behavior based on functional brain activity is a major goal of neuroscience. Numerous studies have been conducted to investigate the relationship between functional brain activity and attention, subject characteristics, autism, psychiatric disorders, and more. By modeling brain activity data as networks, researchers can leverage the mathematical tools of graph and network theory to probe these relationships. In their landmark study, Smith et al. (2015) analyzed the relationship of young adult connectomes and subject measures, using data from the Human Connectome Project (HCP). Using canonical correlation analysis (CCA), Smith et al. found that there was a single prominent CCA mode which explained a statistically significant percentage of the observed variance in connectomes and subject measures. They also found a strong positive correlation of 0.87 between the primary CCA mode connectome and subject measure weights. In this study, we computationally replicate the findings of the original study in both the HCP 500 and HCP 1200 subject releases. The exact computational replication in the HCP 500 dataset was a success, validating our analysis pipeline for extension studies. The extended replication in the larger HCP 1200 dataset was partially successful and demonstrated a dominant primary mode.


2021 ◽  
pp. 2150048
Author(s):  
Hamidreza Namazi ◽  
Avinash Menon ◽  
Ondrej Krejcar

Our eyes are always in search of exploring our surrounding environment. The brain controls our eyes’ activities through the nervous system. Hence, analyzing the correlation between the activities of the eyes and brain is an important area of research in vision science. This paper evaluates the coupling between the reactions of the eyes and the brain in response to different moving visual stimuli. Since both eye movements and EEG signals (as the indicator of brain activity) contain information, we employed Shannon entropy to decode the coupling between them. Ten subjects looked at four moving objects (dynamic visual stimuli) with different information contents while we recorded their EEG signals and eye movements. The results demonstrated that the changes in the information contents of eye movements and EEG signals are strongly correlated ([Formula: see text]), which indicates a strong correlation between brain and eye activities. This analysis could be extended to evaluate the correlation between the activities of other organs versus the brain.


Author(s):  
David López-Sanz ◽  
Jaisalmer de Frutos-Lucas ◽  
Gianluca Susi ◽  
Fernando Maestú

There are two basic ways Magnetoencephalography (MEG) has been applied. The most typical way is recording brain signals related to specific stimuli and tasks or signals indicative of focal pathology as in presurgical brain mapping and epilepsy localization. The second way is recording patterns of spontaneous activity characteristic of particular states or traits. An example of the latter application is described in this chapter that details efforts of deriving brain activity patterns characteristic of Alzheimer’s dementia. The derivation of such patterns will be of great value in diagnosis, prognosis, as well as monitoring progress (or the process of amelioration) of diseases.


Author(s):  
Soomi Lee ◽  
Susan T Charles ◽  
David M Almeida

Abstract Objectives Participating in a variety of daily activities (i.e., activity diversity) requires people to adjust to a variety of situations and engage in a greater diversity of behaviors. These experiences may, in turn, enhance cognitive functioning. This study examined associations between activity diversity and cognitive functioning across adulthood. Method Activity diversity was defined as the breadth and evenness of participation in seven common daily activity domains (e.g., paid work, time with children, leisure, physical activities, volunteering). Participants from the National Survey of Daily Experiences (NSDE: N = 732, Mage = 56) provided activity data during eight consecutive days at Wave 1 (W1) and Wave 2 (W2) 10 years apart. They also provided cognitive data at W2. Results Greater activity diversity at W2 was associated with higher overall cognitive functioning and higher executive functioning at W2. Individuals who increased activity diversity from W1 to W2 also exhibited higher scores in overall cognitive functioning and executive functioning at W2. Overall cognitive functioning, executive functioning, and episodic memory were better in those who had higher activity diversity at both waves, or increased activity diversity from W1 to W2, compared to those who had lower activity diversity or decreased activity diversity over time. Discussion Activity diversity is important for cognitive health in adulthood. Future work can study the directionality between activity diversity and cognitive functioning and underlying social and neurological mechanisms for these associations.


2003 ◽  
Vol 26 (6) ◽  
pp. 672-673
Author(s):  
Valéria Csépe

Brain activity data prove the existence of qualitatively different structures in the brain. However, the question is whether the human brain acts as linguists assume in their models. The modular architecture of grammar that has been claimed by many linguists raises some empirical questions. One of the main questions is whether the threefold abstract partition of language (into syntactic, phonological, and semantic domains) has distinct neural correlates.


Author(s):  
Zara Mansoor ◽  
Mustansar Ali Ghazanfar ◽  
Syed Muhammad Anwar ◽  
Ahmed S. Alfakeeh ◽  
Khaled H. Alyoubi

2001 ◽  
Vol 10 (4) ◽  
pp. 384-400 ◽  
Author(s):  
Luigi Pugnetti ◽  
Michael Meehan ◽  
Laura Mendozzi

The recording and measurement of central and peripheral nervous system responses can provide important information during the development and the application of virtual reality (VR). Although studies on electroencephalographic, evoked potentials, and peripheral psychophysiological changes in connection with VR exposure are still preliminary, they show that reliable data can be obtained even in immersive VR conditions. There is no firm evidence that neurophysiological equipment—sensors and cables—may increase subjects' discomfort and affect their ability to interact with the virtual environments, but additional study is needed to clarify this issue. Suggestions as to how to limit potential interferences are summarized here. Two main lines of research are emerging: one seeking psychophysiological correlates of reaction and adaptation to stimuli and task variables in an attempt to understand more about human-VR interaction, and the other looking for ways to use psychophysiological responses to automatically control aspects of the virtual environments or other external devices. The main results emerging from the first group of studies indicate that psychophysiological measures of brain activity—notably EEG and event-related responses—may be used to distingush between automatic and controlled modes of processing. Additionally, peripheral measures, notably skin-resistance levels, are proposed as objective correlates of presence and of the outcome of specific VR-based desensitization therapies. There is no clear-cut evidence that brain waves may index unwanted effects on the central nervous system of VR exposure, but this issue deserves further study. The results of the second line of research seem to indicate that VR-induced psychophysiological responses can be used to develop assistive devices for people with disabilities or to control hands-free interaction within any virtual environment (for example, in highly demanding conditions). A related and promising field of application is that of neurofeedback, wherein VR may play an important role in increasing the motivational/ attentional span of clients, and, ultimately, the effectiveness of treatment protocols. Given these premises, it is suggested that research on psychophysiological correlates of VR should be incremented along the lines already delineated and possibly include also groups of subjects at risk for adverse affects.


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