| The Brain as Target Image Detector: The Role of Image Category and Presentation Time | | BIBA | Full-Text | 3-12 | |
| Anne-Marie Brouwer; Jan B. F. van Erp; Bart Kappé; Anne E. Urai | |||
| The brain can be very proficient in classifying images that are hard for computer algorithms to deal with. Previous studies show that EEG can contribute to sorting shortly presented images in targets and non-targets. We examine how EEG and classification performance are affected by image presentation time and the kind of target: humans (a familiar category) or kangaroos (unfamiliar). Humans are much easier detected as indicated by behavioral data, EEG and classifier performance. Presentation of humans is reflected in the EEG even if observers were attending to kangaroos. In general, 50ms presentation time decreased markers of detection compared to 100ms. | |||
| Implementation of fNIRS for Monitoring Levels of Expertise and Mental Workload | | BIBAK | Full-Text | 13-22 | |
| Scott C. Bunce; Kurtulus Izzetoglu; Hasan Ayaz; Patricia A. Shewokis; Meltem Izzetoglu; Kambiz Pourrezaei; Banu Onaral | |||
| An accurate measure of mental workload would help improve operational safety
and efficacy in many environments that involve multitasking or sustained
vigilance. The current study utilized functional near-infrared spectroscopy
(fNIRs) to examine the relationship of the hemodynamic response in dorsolateral
prefrontal cortex (DLPFC) as it related to mental workload, level of expertise,
and task performance. DLPFC responses were monitored with fNIRs while 8
participants (4 with high practice, 4 novices) completed a quasirealistic
computerized Warship Commander Task with various levels of difficulty. The
results show that greater expertise was associated with relatively lower
oxygenation (less neural activity) at low to moderate levels of taskload, but
higher oxygenation and better performance at high levels of taskload. For
novices, oxygenation was higher at moderate levels of taskload, but dropped
precipitously at higher levels of taskload, along with performance, consistent
with disengaging from the task. Results are interpreted within a
"scaffolding-storage" framework. Keywords: Optical Brain Imaging; functional near infrared spectroscopy; mental
workload; expertise; practice; fNIR | |||
| Challenges and Solutions with Augmented Cognition Technologies: Precursor Issues to Successful Integration | | BIBAK | Full-Text | 23-29 | |
| Joseph Cohn | |||
| Today's combat environment requires increasingly complex interactions
between human operators and their systems. Whereas in the past, the roles of
human and system were clearly delineated, with the integration of advanced
technologies into the C4ISR toolkit, the distinct parsing of tasks has given
way to paradigms in which the human operator's roles and responsibilities must
dynamically change according to task and context. Yet, current methodologies
for integrating the human into the system have not kept pace with this shift.
An important consequence of this mismatch between human operator and system is
that failures often lead to catastrophic and unrecoverable accidents (O'Connor
& Cohn, 2010). In order to reintegrate the human element back into the
system, new approaches for representing operator performance, in terms of their
individual cognitive and behavioral capacities, limitations and changing needs
are required. Keywords: Neuroscience; Cognition; Autonomy; Human Systems; Information Processing;
Adaptive; Cognitive Architecture | |||
| Augmenting Brain and Cognition by Aerobic Exercise | | BIBAK | Full-Text | 30-38 | |
| Kirk I. Erickson | |||
| Cognitive function declines in late adulthood and this is preceded by
atrophy of the prefrontal cortex, hippocampal formation, and parietal cortex.
Despite significant loss of brain tissue in late adulthood, decline is not
ubiquitous across all older adults. In fact, some adults age quite successfully
with minimal decline. This suggests that brain deterioration might not be an
inevitable consequence of aging. In fact, mounting evidence suggests that
participation in regular aerobic exercise is effective at enhancing cognitive
and brain health in late adulthood. In this paper we discuss the evidence that
cardiorespiratory fitness and aerobic exercise augments cognition by increasing
gray matter volume in prefrontal and hippocampal brain regions. Keywords: Aging; brain; atrophy; exercise | |||
| Neurological Advances and Ethical/Legal Conundrums: Lessons from History | | BIBAK | Full-Text | 39-45 | |
| Cheryl Erwin | |||
| The scientific advances in the neurosciences are exciting and promise to
advance our understanding of the human mind. The ethical and legal issues
raised by neuroscience are distinctive but they are not unique to the
twenty-first century. The ethical issues raised by these technologies deserve
attention even while the science is in development. History teaches us to
reflect on our humanity using insights from many disciplines and many times. Keywords: Neuroethics; neurolaw; neuroprivacy; neuropolicy; research ethics;
regulation of emerging technologies | |||
| Individual Differences and the Science of Human Performance | | BIBAK | Full-Text | 46-54 | |
| Michael Trumbo; Susan M. Stevens-Adams; Stacey M. L. Hendrickson; Robert G. Abbott; Michael Haass; Chris Forsythe | |||
| This study comprises the third year of the Robust Automated Knowledge
Capture (RAKC) project. In the previous two years, preliminary research was
conducted by collaborators at the University of Notre Dame and the University
of Memphis. The focus of this preliminary research was to identify
relationships between cognitive performance aptitudes (e.g., short-term memory
capacity, mental rotation) and strategy selection for laboratory tasks, as well
as tendencies to maintain or abandon these strategies. The current study
extends initial research by assessing electrophysiological correlates with
individual tendencies in strategy selection. This study identifies regularities
within individual differences and uses this information to develop a model to
predict and understand the relationship between these regularities and
cognitive performance. Keywords: Individual Differences; EEG; Memory Span; RAT; Attentional Beam; Mental
Rotation; Ruff Attention Task; Raven's Matrices; Box Folding; Dual Task;
Barton's; Binary; Stroop; N-back; Mismatch Negativity; P300; Oddball; Semantic
Memory; Episodic Memory; Go/No-Go; Flanker; Line Drawing; MAT-B | |||
| Cognition: What Does It Have to Do with the Brain? | | BIBAK | Full-Text | 55-59 | |
| Alexandra Geyer | |||
| The emergence of new non-invasive technologies for assessing the structure
and the function of the human brain has provided us with means to investigate
the neural substrates underlying cognitive processes with the goal of achieving
a better understanding of cognition. This paper is focused on discussing the
contributions that assessment of neural processes underlying cognition brings
to our understanding of cognition as well as the impact of this understanding
of cognition on military operations. Keywords: cognition; neural substrates; intent; warfighters | |||
| The Evolution of Human Systems: A Brief Overview | | BIBAK | Full-Text | 60-66 | |
| Jeff Grubb; Joseph Cohn | |||
| Recently, there has been a profound resurgence interest in expanding the
effectiveness of human machine systems. The motivation for this interest stems
not only from the growing realization that better designed systems -- tailored
to augment their user's innate skills and capabilities -- will enable users to
'do more', but also from the fact that the world with which we interact is
becoming increasingly reliant on machines. In the past, the human machine
interface was bridged through engineering based principles, but, with our
expanding understanding of how the human brain drives behavior it is now
possible to consider, as never before, human machine design efforts that fully
address human and machine needs at the same time. Keywords: Neuroscience; Cognition; Automation; Human Systems; Cognitive Model | |||
| The Influence of Culture on Memory | | BIBAK | Full-Text | 67-76 | |
| Angela H. Gutchess; Aliza J. Schwartz; Aysecan Boduroglu | |||
| The study of cognition across cultures offers a useful approach to both
identifying bottlenecks in information processing and suggesting
culture-specific strategies to alleviate these limitations. The recent emphasis
on applying cognitive neuroscience methods to the study of culture further aids
in specifying which processes differ cross-culturally. By localizing cultural
differences to distinct neural regions, the comparison of cultural groups helps
to identify candidate information processing mechanisms that can be made more
efficient with augmented cognition and highlights the unique solutions that
will be required for different groups of information processors. Keywords: cognition; culture; memory; strategies; fMRI | |||
| Using Computational Modeling to Assess Use of Cognitive Strategies | | BIBAK | Full-Text | 77-86 | |
| Michael J. Haass; Laura E. Matzen | |||
| Although there are many strategies and techniques that can improve memory,
cognitive biases generally lead people to choose suboptimal memory strategies.
In this study, participants were asked to memorize words while their brain
activity was recorded using electroencephalography (EEG). The participants'
memory performance and EEG data revealed that a self-testing (retrieval
practice) strategy could improve memory. The majority of the participants did
not use self-testing, but computational modeling revealed that a subset of the
participants had brain activity that was consistent with this optimal strategy.
We developed a model that characterized the brain activity associated with
passive study and with explicit memory testing. We used that model to predict
which participants adopted a self-testing strategy, and then evaluated the
behavioral performance of those participants. This analysis revealed that, as
predicted, the participants whose brain activity was consistent with a
self-testing strategy had better memory performance at test. Keywords: Memory; computational modeling; electroencephalography | |||
| Advances and Challenges in Signal Analysis for Single Trial P300-BCI | | BIBA | Full-Text | 87-94 | |
| Kun Li; Vanitha Narayan Raju; Ravi Sankar; Yael Arbel; Emanuel Donchin | |||
| In this paper a brief introduction to some of the goals, recent developments, and open problems in BCI research are given. We mainly focus on presenting our research work in signal processing for single-trial P300-BCI and discuss our current plans for improving the BCI method. | |||
| Characterizing the Performance Limits of High Speed Image Triage Using Bayesian Search Theory | | BIBAK | Full-Text | 95-103 | |
| Santosh Mathan; Kenneth E., II Hild; Yonghong Huang; Misha Pavel | |||
| The rapid serial visual presentation (RSVP) modality has been used in
conjunction with neurophysiological and behavioral responses to identify
targets within large volumes of imagery efficiently. The research reported here
uses optimal search theory to characterize the limits of this approach. Search
theory is used to inform the estimation of detection functions. These functions
provide a principled basis for selecting presentation parameters that balance
search efficiency and accuracy. Detection functions are also used to
characterize individual differences in search performance and to assess the
extent to which the RSVP presentation modality generalizes across a class of
complex targets. Keywords: EEG; Search Theory; Rapid Serial Visual Presentation; Visual Psychophysics;
Detection Functions; Target Detection | |||
| Facial Recognition: An Enabling Technology for Augmented Cognition Applications | | BIBAK | Full-Text | 104-111 | |
| Denise M. Nicholson; Christine Podilchuk; Kathleen Bartlett | |||
| Research in Augmented Cognition (AugCog) investigates computational methods,
technologies, and non-invasive neurophysiological tools to adapt computational
systems to the changing cognitive state of human operators to improve task
performance. Closed-loop AugCog systems contain four components: 1) operational
or simulated environment, 2) automated sensors to monitor and assess cognitive
state via behavior and/or physiology, 3) adaptive interface, and 4)
computational decision architecture that directs AugCog adaptations. Since
cognitive state is influenced by environment, a critical challenge for AugCog
systems is capture of situational awareness (SA) within the decision
architecture. Previously, AugCog systems have been demonstrated within
simulated environments that provide SA and ground truth data to drive
intelligent decision architecture. In live operating environments, electronic
C4 systems (i.e., communications), provide a limited model of operator "state,"
but emerging facial recognition/analysis technology can provide detection,
identification, and tracking of humans in the environment to increase the
accuracy of the AugCog system's SA. Keywords: Augmented Cognition; facial recognition; situation awareness; biometrics;
environmental monitoring | |||
| Analysis of Multiple Physiological Sensor Data | | BIBAK | Full-Text | 112-119 | |
| Lauren Reinerman-Jones; Grant Taylor; Keryl Cosenzo; Stephanie J. Lackey | |||
| Physiological measures offer many benefits to psychological research
including objective, non-intrusive assessment of affective and cognitive
states. However, this utility is limited by analysis techniques available for
testing data recorded by multiple physiological sensors. The present paper
presents one set of data that was attained from a repeated measures design with
a nominal independent variable for analysis. Specifically, the International
Affective Picture System (IAPS; Lang, Bradley, & Cuthbert, 2008), a series
of images known to convey seven different emotions, was presented to
participants while measures of their neurological activity
(Electroencephalogram; EEG), heart rate (Electrocardiogram; ECG), skin
conductance (Galvanic Skin Respond; GSR), and pupillary response were taken.
Subsequently, a discussion of statistics available for analyzing responses
attained from the various sensors is presented. Such statistics include
correlation, ANOVA, MANOVA, regression, and discriminant function analysis. The
details on design limitations are addressed and recommendations are given for
employing each statistical option. Keywords: EEG; ECG; Eye Tracking; Statistical Analyses; Emotion | |||
| Exploring New Methodologies for the Analysis of Functional Magnetic Resonance Imaging (fMRI) Following Closed-Head Injuries | | BIBAK | Full-Text | 120-128 | |
| Peter B. Walker; Ian N. Davidson | |||
| An increasing amount of research has focused on the use of newer and
alternative data analytic approaches to multi-dimensional data sets. The
primary aim of this paper is to introduce two data analytic approaches as they
have been applied to image scans from functional Magnetic Resonance Imaging
(fMRI). The first approach involves loading data from fMRI scans into
multi-dimensional cubes and performing tensor decomposition. In addition, we
introduce a second approach involving the use of network modeling that attempts
to identify stable networks in fMRI scans across time. Discussion will be
focused on the application of these approaches to the modeling and
rehabilitation following closed-head injury. Keywords: fMRI; Tensor Decomposition; Graph/Network Modeling | |||
| EEG Knows Best: Predicting Future Performance Problems for Targeted Training | | BIBAK | Full-Text | 131-136 | |
| Gwendolyn E. Campbell; Christine L. Belz; Charles P. R. Scott; Phan Luu | |||
| Many uses for neurophysiological data in training have been proposed in the
literature [6], [10], and [11]. However, to date it has not been demonstrated
that the use of EEG yields performance diagnoses that are actually more
accurate. The current study investigated the capability of EEG to accurately
diagnose performance difficulties by examining the predictive ability of an
accurate diagnosis on future performance. The data from this study suggests
that using EEG to filter a trainee's performance data prior to analysis on a
computer based tank identification task yields a more accurate diagnosis than
analyzing the data with the traditional statistical methods. Keywords: electroencephalography; training; neurophysiology | |||
| Computational Cultural Neuroscience: Implications for Augmented Cognition | | BIBAK | Full-Text | 137-142 | |
| Joan Y. Chiao | |||
| From perceiving objects in space to recognizing emotions at a distance,
culture affects how people think, feel, reason as well as the neurobiological
mechanisms underlying these processes. Here I review recent evidence from
cultural neuroscience, introduce the notion of computational cultural
neuroscience -- the development of computational and formal models of how
culture affects neurobiological mechanisms and vice versa -- and finally,
discuss the implications of computational cultural neuroscience for research in
augmented cognition. Keywords: cultural neuroscience; computational cultural neuroscience; augmented
cognition | |||
| Enhancing Team Performance Using Neurophysiologic Synchronies in a Virtual Training Environment | | BIBAK | Full-Text | 143-152 | |
| Marianne Clark; Kimberly Cellucci; Chris Berka; Daniel J. Levendowski; Jonny Trejo; Amy Kruse; Ron Stevens | |||
| A study was conducted to investigate the use of neurophysiologic synchronies
as a measurement of team cognition (1) in a military-style virtual environment
simulation. Neurophysiologic synchronies (NS), defined as the second-by-second
quantitative co-expression of the levels of cognitive measures by individual
members of a team (8), were found to be useful in monitoring the quality of
teamwork and to be a means to identify more optimal patterns of team
interaction which can be used to provide feedback during training. In the
current study, findings showed promise for further research in the collection
of NS. A framework is also proposed to support the research and training of
team cognition. Keywords: Team performance; team cognition; shared mental models; collaboration;
neurophysiologic synchronies; electroencephalography (EEG); virtual
environments; mission rehearsal training; RealWorld | |||
| Theoretical Transpositions in Brain Function and the Underpinnings of Augmented Cognition | | BIBA | Full-Text | 153-158 | |
| Cali M. Fidopiastis | |||
| Augmented Cognition (AugCog) explores behavior in real-time and in real world settings. This research avenue is a departure from standard experimental approaches such as those accepted in the fields of Cognitive Psychology and the Neurosciences. AugCog as a field of study, therefore, has the potential to up-end some of the tried-and-true laboratory based findings on such topics as learning and transfer of learning. Steeped in history from both the biological systems perspective and the cognition neuroscience vantage, the future of AugCog seems contingent on its success at merging these paradigms and concurrently producing analysis tools with which to keep peering into the brain as it functions in operational environments. In this paper, we review the theories that drive Augmented Cognition approaches and evaluate their capacity to keep the field moving forward. | |||
| Non-invasive Functional Brain Biomarkers for Cognitive-Motor Performance Assessment: Towards New Brain Monitoring Applications | | BIBAK | Full-Text | 159-168 | |
| Rodolphe J. Gentili | |||
| Along with theoretical advances in neuroscience research, recent
neurotechnological developments provide portable recording and processing
systems that can be employed for real-time assessment in applied military
environments. This article provides a brief overview of research related to
non-invasive brain biomarkers derived from brain signals that can track brain
dynamics during cognitive-motor performance. Potential applications of such
brain biomarkers for military personnel such as neurofeedback for accelerated
learning as well as brain monitoring for performance assessment and
rehabilitation are discussed. Keywords: Cognitive-motor performance; EEG/fNIRS biomarkers; alpha power; phase
synchronization; brain monitoring; neurofeedback; rehabilitation | |||
| Estimating the Level of Motion Sickness Based on EEG Spectra | | BIBAK | Full-Text | 169-176 | |
| Li-Wei Ko; Chun-Shu Wei; Tzyy-Ping Jung; Chin-Teng Lin | |||
| Motion sickness (MS) is a normal response to real, perceived, or even
anticipated movement. People tend to get motion sickness on a moving boat,
train, airplane, car, or amusement park rides. Although many motion
sickness-related biomarkers have been identified, but how to estimate human's
motion sickness level (MSL) is a big challenge in the operational environment.
Traditionally, questionnaire and physical check are the common ways to
passively evaluate subject's sickness level. Our past studies had investigated
the EEG activities correlated with motion sickness in a virtual-reality based
driving simulator. The driving simulator comprised an actual automobile mounted
on a Stewart motion platform with six degrees of freedom, providing both visual
and vestibular stimulations to induce motion-sickness in a manner that is close
to that in daily life. EEG data were acquired at a sampling rate of 500 Hz
using a 32-channel EEG system. The acquired EEG signals were analyzed using
independent component analysis (ICA) and time-frequency analysis to assess EEG
correlates of motion sickness. Subject's degree of motion-sickness was
simultaneously and continuously reported using an onsite joystick, providing
non-stop psychophysical references to the recorded EEG changes. We found that
the parietal, motor, occipital brain regions exhibited significant EEG power
changes in response to vestibular and visual stimuli. Based on these findings
and experimental results, this study aims to develop an EEG-based system to
estimate subject's motion sickness level upon the EEG power spectra from
motion-sickness related brain areas. The MS evaluation system can be applied to
early detection of the subject's motion sickness and prevent its uncomfortable
syndromes in our daily life. Furthermore, the experiment results could also
lead to a practical human-machine interface for noninvasive monitoring of
motion sickness of drivers or passengers in real-world environments. Keywords: EEG; ICA; motion-sickness; estimation; time-frequency; driving cognition | |||
| Combining fNIRS and EEG to Improve Motor Cortex Activity Classification during an Imagined Movement-Based Task | | BIBA | Full-Text | 177-185 | |
| Darren J. Leamy; Rónán Collins; Tomás Ward | |||
| This work serves as an initial investigation into improvements to classification accuracy of an imagined movement-based Brain Computer Interface (BCI) by combining the feature spaces of two unique measurement modalities: functional near infrared spectroscopy (fNIRS) and electroencephalography (EEG). Our dual-modality system recorded concurrent and co-locational hemodynamic and electrical responses in the motor cortex during an imagined movement task, participated in by two subjects. Offline analysis and classification of fNIRS and EEG data was performed using leave-one-out cross-validation (LOOCV) and linear discriminant analysis (LDA). Classification of 2-dimensional fNIRS and EEG feature spaces was performed separately and then their feature spaces were combined for further classification. Results of our investigation indicate that by combining feature spaces, modest gains in classification accuracy of an imagined movement-based BCI can be achieved by employing a supplemental measurement modality. It is felt that this technique may be particularly useful in the design of BCI devices for the augmentation of rehabilitation therapy. | |||
| The Frustration Status and Noise Proof Feature During Perception of the Auditory Images | | BIBAK | Full-Text | 186-193 | |
| Sergey Lytaev; Yuliaj Surovitskaj | |||
| Tests for modeling of the human status at recognition of target and non
target stimulus with auditory evoked potentials (AEPs) registration; emotional
neutral and significant information-psychological influences with EEG
registration and analysis of fractal dynamics (AFD) were applied. From the
moment of signal presentation the greatest difference of AEPs at target
stimulation is marked in frontal areas of the left hemisphere through 16-18 ms.
Emotionally-neutral and emotionally-significant psycho-informational influences
provided the most conclusive AFD EEG data. Essentially, personal frustration is
activated when the subject perceives situations to be threatening to his or her
self-esteem and self-evaluation. Individuals with high levels of frustration
are inclined to perceive a wide range of situations as threatening and
therefore, will respond according to what they think the situation dictates. Keywords: Auditory Evoked Potentials (AEPs); Brain Mapping; EEG;
Information-Psychological Influences | |||
| Cultural Neuroscience and Individual Differences: Implications for Augmented Cognition | | BIBAK | Full-Text | 194-198 | |
| Laura E. Matzen | |||
| Technologies that augment human cognition have the potential to enhance
human performance in a wide variety of domains. However, there are a number of
individual differences in brain activity that must be taken into account during
the development, validation, and application of augmented cognition tools. A
growing body of research in cultural neuroscience has shown that there are
substantial differences in how people from different cultural backgrounds
approach various cognitive tasks. In addition, there are many other types of
individual differences and even changes in a single individual over time that
have implications for augmented cognition research and development. The aim of
this session is to highlight a few of those differences and to discuss how they
might impact augmented cognition technologies. Keywords: Cultural neuroscience; individual differences | |||
| Towards a Software Toolkit for Neurophysiological Data Collection and Analysis | | BIBA | Full-Text | 199-202 | |
| James Niehaus; Peter Weyhrauch | |||
| Modern devices such as cell phones, handheld computers, and technical equipment enable professional users to communicate, understand, and act more efficiently and effectively. However, these new systems often increase cognitive workload, and may even introduce performance errors. System analysts can decrease these errors by identifying a users cognitive performance deficits and addressing them through training, improved performance support, and redesigned operational systems. To identify these deficits, neurocognitive measurements of indicators such as cognitive workload and attention can be approximated with high accuracy by using non-invasive sensors to measure brain activity and other physiological indicators. Thus, we are designing and demonstrating the feasibility of a toolkit for system analysts to use neurocognitive measurements to recommend additional training for individual users, performance support for all users of the system, and the redesign of system interfaces or components. This research addresses a clear need for an extensible, general-purpose, stand-alone neurocognitive assessment toolkit that can be incorporated into new and existing technology development with little to no integration effort. | |||
| From Sound to Meaning: Changes in EEG Source-Localized Brain Activity with Foreign-Language Training | | BIBAK | Full-Text | 203-211 | |
| Catherine Poulsen; Phan Luu; Colin Davey; Don M. Tucker; Joey Nelson | |||
| Learning a foreign language is a complex human task, involving multiple
processes and a dynamic network of brain activity. The present study used
256-channel dense-array electroencephalography (dEEG) and linear-inverse source
analysis (sLORETA) to identify changes in brain activity during the early
stages of language training. Twenty native English speakers attended two
50-minute sessions of computer-assisted, virtual-reality Dari language
instruction. Training-specific changes in neural activity were observed in both
articulatory-motor and semantic processing regions, including increases in left
posterior inferior temporal gyrus and left lateral inferior frontal regions.
Also observed was increasing left lateralization, and an increase in
mediotemporal regions suggestive of memory reconsolidation. These findings
illustrate the ability to track changes with training in recognized
language-processing brain regions using source-localized EEG recorded while
listening to continuous, naturalistic speech. Subsequent research will explore
individual differences and the development of adaptive training based on neural
indices. Keywords: language learning; training; dense-array EEG; linear-inverse source
analysis; electroencephalography; event-related potentials | |||
| Analyzing Neural Correlates of Attentional Changes during the Exposure to Virtual Environments: Application of Transcranial Doppler Monitoring | | BIBAK | Full-Text | 212-220 | |
| Beatriz Rey; Vera Parkhutik; José Tembl; Mariano Alcañiz Raya | |||
| Transcranial Doppler monitoring (TCD) has been proposed as a tool to be used
in Augmented Cognition (AugCog) systems to monitor brain activation during the
performance of different cognitive tasks. In the present study, the main goal
is to analyze variations in blood flow velocity (BFV) measured by TCD during
the exposure to a virtual reality environment when there are changes in the
focus of attention of the participants. Two abrupt events are forced during the
navigation in a virtual environment in order to change their focus of attention
to the real world. In one of them, the screen goes completely blue, and in the
other one, a mesh appears in front of the virtual environment making it
difficult to visualize. Results show that BFV values in both middle cerebral
arteries remain similar when the first event occurs, but there is an increase
during the second event. The origin of this increment may probably be found in
the higher difficulty of having a mesh in front of the virtual environment,
requiring more attention than before. These results show that changes in the
stimuli can generate modifications in BFV that can be monitored by TCD, and can
be useful for AugCog applications. Keywords: Augmented Cognition; Virtual Reality; Transcranial Doppler;
Neurophysiological Data; Cognitive State Assessment | |||
| Neuroergonomic Assessment of Simulator Fidelity in an Aviation Centric Live Virtual Constructive (LVC) Application | | BIBAK | Full-Text | 221-230 | |
| Tom Schnell; Alex Postnikov; Nancy Hamel | |||
| This paper describes a recent human factors study that was performed on a
flight simulator and in a fighter trainer jet aircraft to quantify the
cognitive effects of simulator fidelity. There are many parameters that could
be manipulated to affect physical fidelity in a simulator and we want to point
out that in this study we make no claims of having covered a large portion of
the possible fidelity design space. Rather, this study provides a comparison of
trainee performance in a low to mid-level simulator with the performance
obtained in a real fighter jet training aircraft using state-of-the-art
operator state characterization equipment. As this study is ongoing, only
partial data is shown in this paper. Keywords: Neurocognitive measures; operator state characterization; flight training | |||
| Brain Activity of Young and Adult Hebrew Speakers during Lexical Decision Task: fNIR Application to Language | | BIBAK | Full-Text | 231-239 | |
| Itamar Sela; Tzipi Horowitz-Kraus; Meltem Izzetoglu; Patricia A. Shewokis; Kurtulus Izzetoglu; Banu Onaral; Zvia Breznitz | |||
| The process of reading activates a large-scale neural network which includes
different cortical brain regions. This network is thought to be age-dependent
and changes throughout the process of reading acquisition. The frontal lobe is
considered to be related to higher, executive, functions. We conducted a
functional Near InfraRed Spectroscopy (fNIR) study in order to compare frontal
lobe performance during a Lexical Decision Task (LDT) among two different
age-groups: children and adults. Data indicated significant differences with
age in LDT behavioral performance, and brain activity in the upper left frontal
lobe. The young group exhibited slower reaction times and lower accuracy in
addition to differences both in the level of blood oxygenation as well in the
blood oxygenation timeline. The current study's results suggest 1) the
involvement of the frontal lobe during the process of reading and that 2)
frontal lobe activity is modified with the age of maturity. Keywords: Neuroimaging; fNIR; Lexical Decision Task; Developmental language | |||
| Brain in the Loop: Assessing Learning Using fNIR in Cognitive and Motor Tasks | | BIBAK | Full-Text | 240-249 | |
| Patricia A. Shewokis; Hasan Ayaz; Meltem Izzetoglu; Scott C. Bunce; Rodolphe J. Gentili; Itamar Sela; Kurtulus Izzetoglu; Banu Onaral | |||
| The skill acquisition process and learning assessments are dependent upon
the quality and extent of practice of the tasks. Typically, learning is
inferred from behavioral and cognitive results without taking into account the
role of the brain in the learning loop. In this paper we discuss the neural
mechanisms of learning and skill acquisition using fNIR with 3D spatial
navigation tasks (e.g., MazeSuite), a center-out reaching movement task during
which adaptation to new tool use was performed and mathematical problem solving
tasks. Further, this research study compared and contrasted multiple analysis
methods, which include general linear models of repeated measures during
acquisition, retention and transfer phases of learning, learning curve
analyses, the testing of fit of various learning models (i.e., power,
exponential or other non-linear functions) and relationships between neural
activation and behavioral measures. Keywords: Practice; Learning; Optical Brain Imaging; Analysis Methods; Functional Near
Infrared Spectroscopy; fNIR; Prefrontal Cortex | |||
| Neurocognitive Patterns: Using Brain, Behavior, and Context to Infer User Intent | | BIBAK | Full-Text | 250-256 | |
| Webb Stacy | |||
| Neurocognitive Patterns is a system that will offer execution options to
users as soon as they form an intention to act. It will accomplish this by
combining neural signals, user behavior, and contextual knowledge to determine
when a user has a goal, and what that goal is. Because it will leverage the
user's neural signals and behavioral history, the options it will provide to
the user will be available quickly. Because it will leverage real-time
contextual and background knowledge, its estimates concerning the user's goal
will be accurate. Our initial target domain is UAV operators, but we expect it
will be of use to other military decision-makers in Command and Control
settings. We also expect that Neurocognitive Patterns will be a useful tool in
Cognitive Neuroscience in general for interpreting neural signals in the
presence of salient contextual information. Keywords: Neural Signals; Behavioral Measures; User Intent; Using Contextual
Information | |||
| Behavioral and Brain Dynamics of Team Coordination Part I: Task Design | | BIBAK | Full-Text | 257-264 | |
| Emmanuelle Tognoli; A. J. Kovacs; B. Suutari; Daniel Afergan; Joseph T. Coyne; G. Gibson; Roy Stripling; J. A. Scott Kelso | |||
| In this study, pairs of subjects performed a team-intensive task with the
shared goal of clearing a virtual room from threats. Our goal was to identify
signatures of efficient team work from a dynamic analysis of both subjects'
brain signals and behavioral performance. An ecologically valid task of room
clearing was designed and a novel analysis framework was developed to address
the challenge of understanding complex, continuous social processes at both
behavioral and brain levels. In the present paper, we detail the design of the
task, and present validation techniques undertaken to acquire and analyze
high-quality and accurately timed neurobehavioral information. A companion
paper will discuss the neurobehavioral findings and their implications. Keywords: Neuromarkers; EEG; neurobehavioral dynamics; social behavior; complexity | |||
| Using Neurophysiological Data to Inform Feedback Timing: A Pilot Study | | BIBAK | Full-Text | 265-274 | |
| Jennifer J. Vogel-Walcutt; Julian Abich | |||
| In an effort to achieve a level of knowledge comparable to that which
typically results from individual tutoring, innovative models of adaptive
computer-based training are continually being tested and refined. Despite these
efforts, adaptive computerized training programs still fall significantly short
of the gold standard of one-on-one instruction. In response, this study used a
previously developed model defining when to apply instructional feedback during
learning in order to improve efficiency. Specifically, we compared the
combination of performance and neuro-physiological indices to performance alone
as indicators for when to adapt training. Contrary to our hypotheses, this
study failed to demonstrate positive impact on knowledge acquisition, knowledge
application, perceived cognitive load, or training efficiency. However, based
on observational data, it is suspected that participants in neither group
possessed enough available working memory capacity to attend to the supporting
material. Consequently, this may account for the lack of differential findings. Keywords: Feedback; EEG; physiological measures; simulation based training; adaptive
intelligent systems | |||
| Modelling User Behaviour and Interactions: Augmented Cognition on the Social Web | | BIBA | Full-Text | 277-287 | |
| Ching-man Au Yeung; Tomoharu Iwata | |||
| Social sharing on the Web has become very popular in recent years. However, as the amount of information grows rapidly it becomes difficult for a user to discover relevant information. The principle of augmented cognition can be applied to help users on the Social Web. This can be done by modelling the behaviours and interactions of the users in a system in order to discover implicit relations among the users. We describe two related approaches to model user behaviours for different types of social sharing sites. We show that the methods can be used to help users identify social relations that are more important to them, as well as items that are more relevant to their interests. | |||
| Brain Signatures of Team Performance | | BIBAK | Full-Text | 288-297 | |
| Silke Dodel; Joseph Cohn; Jochen Mersmann; Phan Luu; Chris Forsythe; Viktor Jirsa | |||
| We report results from a dual electroencephalography (EEG) study, in which
two-member teams performed a simulated combat scenario. Our aim was to
distinguish expert from novice teams by their brain dynamics. Our findings
suggest that dimensionality increases in the joint brain dynamics of the team
members is a signature of increased task demand, both objective, e.g. increased
task difficulty, and subjective, e.g. lack of experience in performing the
task. Furthermore in each team we identified a subspace of joint brain dynamics
related to team coordination. Our approach identifies signatures specific to
team coordination by introducing surrogate team data as a baseline for joint
brain dynamics without team coordination. This revealed that team coordination
affects the subspace itself in which the joint brain dynamics of the team
members are evolving, but not its dimensionality. Our results confirm the
possibility to identify signatures of team coordination from the team members'
brain dynamics. Keywords: team; coordination; manifold; dimension; brain; dynamics; subspace; EEG | |||
| Team Coordination Dynamics and the Interactive Approach: Emerging Evidence and Future Work | | BIBAK | Full-Text | 298-307 | |
| Jamie C. Gorman | |||
| In the study of coordination and teamwork, the primacy of team interaction
is emphasized in an interactive approach. The interactive approach lies in
stark contrast to the traditional, shared cognition approach to understanding
team cognition. An overview of team coordination dynamics, an interactive
approach rooted in nonlinear dynamics, is provided. Results from a series of
experiments on team coordination dynamics are summarized. Finally, future
research directions, inspired by those results, are considered. Keywords: Nonlinear dynamics; Teams; Team coordination; Teamwork | |||
| Performance-Based Metrics for Evaluating Submarine Command Team Decision-Making | | BIBAK | Full-Text | 308-317 | |
| Eric Jones; Ronald Steed; Frederick Diedrich; Robert Armbruster; Cullen Jackson | |||
| Successful submarine operations -- those that accomplish the mission while
maintaining security and safety -- depend on numerous factors, including the
capabilities of various sensor systems, the reliability of algorithms, and the
proficiency of the crew. Among the most critical elements is Command Team
decision-making and the underlying processes that create a cohesive and
effective team. As a team, submarine commanders must successfully contend with
complexities associated with safety and security as they build an understanding
of the operational environment in order to accomplish their mission. Hence,
opportunities to enhance training to support Command Team decision-making are
essential. This paper describes a framework used to develop performance
measures to support formative assessment of the submarine Command Team. Results
are reported here from a study at the Naval Submarine School concerning the
validity and utility of the measures in relation to capturing essential aspects
of performance. Keywords: performance measures; formative assessment; decision-making; teamwork;
submarine | |||
| Multi-Modal Measurement Approach to Team Cohesion | | BIBAK | Full-Text | 318-324 | |
| Camilla C. Knott; Alexandra Geyer; Jason Sidman; Emily Wiese | |||
| Team performance is a function, in part, of team cohesion: a dynamic process
that is reflected in the tendency of a group to remain united in the pursuit of
its goals and objectives (Carron 1982). We propose that a multi-modal
measurement approach that integrates data from a variety of sources is critical
to forming a comprehensive understanding of the relationship between team
cohesion and performance, and can afford measurement of the hard-to-assess
social component of team cohesion. Moreover, the use of a multi-modal
measurement technique can afford flexibility in measuring across a variety of
environments and selecting the most relevant measurement tools to minimize the
technical footprint required for the assessment of teams and individuals in an
operational environment. Keywords: Team cohesion; multi-modal measurement; team performance | |||
| Communications-Based Automated Assessment of Team Cognitive Performance | | BIBA | Full-Text | 325-334 | |
| Kiran Lakkaraju; Susan M. Stevens-Adams; Robert G. Abbott; Chris Forsythe | |||
| In this paper we performed analysis of speech communications in order to determine if we can differentiate between expert and novice teams based on communication patterns. Two pairs of experts and novices performed numerous test sessions on the E-2 Enhanced Deployable Readiness Trainer (EDRT) which is a medium-fidelity simulator of the Naval Flight Officer (NFO) stations positioned at bank end of the E-2 Hawkeye. Results indicate that experts and novices can be differentiated based on communication patterns. First, experts and novices differ significantly with regard to the frequency of utterances, with both expert teams making many fewer radio calls than both novice teams. Next, the semantic content of utterances was considered. Using both manual and automated speech-to-text conversion, the resulting text documents were compared. For 7 of 8 subjects, the two most similar subjects (using cosine-similarity of term vectors) were in the same category of expertise (novice/expert). This means that the semantic content of utterances by experts was more similar to other experts, than novices, and vice versa. Finally, using machine learning techniques we constructed a classifier that, given as input the text of the speech of a subject, could identify whether the individual was an expert or novice with a very low error rate. By looking at the parameters of the machine learning algorithm we were also able to identify terms that are strongly associated with novices and experts. | |||
| Visual Analytics of Social Networks: Mining and Visualizing Co-authorship Networks | | BIBAK | Full-Text | 335-345 | |
| Carson Kai-Sang Leung; Christopher L. Carmichael; Eu Wern Teh | |||
| Co-authorship networks are examples of social networks, in which researchers
are linked by their joint publications. Like many other instances of social
networks, co-authorship networks contain rich sets of valuable data. In this
paper, we propose a visual analytic tool, called SocialVis, to analyze and
visualize these networks. In particular, SocialVis first applies frequent
pattern mining to discover implicit, previously unknown and potential useful
social information such as teams of multiple frequently collaborating
researchers, their composition, and their collaboration frequency. SocialVis
then uses a visual representation to present the mined social information so as
to help users get a better understanding of the networks. Keywords: Human-computer interaction; data mining; frequent patterns; social network
analysis and mining; social computing; social information; data visualization;
information and knowledge visualization; visualizing social interaction;
augmented cognition | |||
| The Crowdsourcing Design Space | | BIBAK | Full-Text | 346-355 | |
| Yasuaki Sakamoto; Yuko Tanaka; Lixiu Yu; Jeffrey V. Nickerson | |||
| Crowdsourcing is a new kind of organizational structure, one that is
conducive to large amounts of short parallel work: thousands of individuals may
work for several minutes on tasks, their outputs aggregated into a useful
product or service. The dimensions of this new organizational form are
described. Areas for future research are identified, focusing on open-ended
tasks and the coordination structures that might foster collective creativity. Keywords: Crowdsourcing; distributed cognition; organizational design; peer
production; collective creativity; human computation | |||
| Developing Systems for the Rapid Modeling of Team Neurodynamics | | BIBAK | Full-Text | 356-365 | |
| Ronald H. Stevens; Trysha Galloway; Chris Berka; Peter Wang | |||
| Cognitive Neurophysiologic synchronies (NS) are a low level data stream
derived from EEG measurements that can be collected and analyzed in near real
time and in realistic settings. We are using NS to develop systems that can
rapidly determine the functional status of a team with the goals of being able
to assess the quality of a teams' performance / decisions, and to adaptively
rearrange the team or task components to better optimize the team. EEG-derived
measures of engagement from Submarine Piloting and Navigation team members were
normalized and pattern classified by self-organizing artificial neural networks
and hidden Markov models. The temporal expression of these patterns were mapped
onto team events and related to the frequency of team members' speech.
Standardized models were created using pooled data from multiple teams and were
used to compare NS expression across teams, training sessions and levels of
expertise. These models have also been incorporated into software systems that
can provide for rapid (minutes) after training feedback to the team and provide
a framework for future real-time monitoring. Keywords: Collaboration; EEG; Neurophysiologic synchrony | |||
| Mapping Cognitive Attractors onto the Dynamic Landscapes of Teamwork | | BIBAK | Full-Text | 366-375 | |
| Ronald H. Stevens; Jamie C. Gorman | |||
| The objective of this study was to apply ideas from complexity theory to
derive new models of teamwork. The measures include EEG-derived measures of
Engagement and Workload obtained from submarine piloting and navigation (SPAN)
teams and communication streams from Uninhibited Air Vehicle Synthetic Task
Environments (UAV-STE). We show that despite large differences in the data
streams and modeling, similar changes are seen in the respective order
parameters in response to task perturbations and the experience of the team.
These changes may provide a pathway for future adaptive training systems as
both order parameters could conceivably be modeled and reported in real time. Keywords: Complexity; Teamwork; EEG; Neurophysiologic synchrony; Nonlinear dynamics | |||
| Behavioral and Brain Dynamics of Team Coordination Part II: Neurobehavioral Performance | | BIBAK | Full-Text | 376-382 | |
| Emmanuelle Tognoli; A. J. Kovacs; B. Suutari; Daniel Afergan; Joseph T. Coyne; G. Gibson; Roy Stripling; J. A. Scott Kelso | |||
| In this study, pairs of subjects performed a team-intensive task with the
shared goal of clearing a virtual room from threats. The neurobehavioral
dynamics of both subjects was analyzed to identify signatures of efficient team
work. An ecologically valid task of room clearing was designed and a novel
analysis framework was developed to address the challenge of understanding
complex, continuous social processes at both behavioral and brain levels. A
companion paper detailed the design of the neurobehavioral task and its
associated dynamical analysis framework. In this paper, we present candidate
neuromarkers for efficient room clearing and discuss key theoretical issues
relating to successful team coordination. Keywords: Neuromarkers; EEG; neurobehavioral dynamics; social behavior; complexity | |||
| Feature Selection in Crowd Creativity | | BIBAK | Full-Text | 383-392 | |
| Lixiu Yu; Yasuaki Sakamoto | |||
| Crowdsourcing is emerging as a wellspring of creative designs. This paper
examines the mechanisms that support collective design. A sequential
combination system is described: one crowd generates designs, and another crowd
combines these designs. Previous experiments showed that the combined designs
were judged more creative than the initial designs. The current work extends
this previous research by examining the combination process of the designs more
closely, looking at how features of the designs were selected and integrated
into later designs. Participants preferred atypical features to typical ones
for integration, and given a choice, selected practical but less atypical
features over impractical but more atypical features. We conclude that crowds
attend to both novelty and practicality of the features, and that the presence
of atypical yet practical features contributes to the increased creativity of
the combined designs. Keywords: Crowdsourcing; collective creativity; combination; feature selection | |||
| Augmented Cognition Methods for Evaluating Serious Game Based Insider Cyber Threat Detection Training | | BIBAK | Full-Text | 395-403 | |
| Terence S. Andre; Cali M. Fidopiastis; Tiffany R. Ripley; Anna L. Oskorus; Ryan E. Meyer; Robert A. Snyder | |||
| DoD investments into cyber threat defense are ongoing; however, little
attention is paid to training personnel to detect and prevent threats to cyber
networks that come from internal sources. Supervisors need to know what
behavioral signs to watch for that might indicate an employee intends to commit
an insider crime. Monitoring employee workstations is proving an ineffective
means of determining insider threats. Training is needed to provide examples of
the numerous ways cyber threats are achieved. An interactive role-play game
environment may provide an appropriate instructional delivery system to train
supervisors. Such a training system should employ instructional support
features, aids, and feedback to the trainer and the trainee. The training
system should also provide adaptive learning pathways to facilitate accelerated
learning where individual assessments show mastery of specific content.
Creating such a system not only requires appropriate training materials, but
also a means to assess the systems efficacy. Augmented cognition methods and
techniques for evaluating the cognitive state of a learner provide a real-time,
objective means of evaluating training delivery and content. In this paper we
discuss our efforts to assess learner engagement using psychophysiological
measures. Keywords: accelerated learning; adaptive training; learner engagement; psychophysical
measures | |||
| Ongoing Efforts towards Developing a Physiologically Driven Training System | | BIBAK | Full-Text | 404-412 | |
| Joseph T. Coyne; Ciara Sibley; Carryl Baldwin | |||
| There have been a number of successes of real-time application of
physiological measures in operational environments such as with the control of
remotely piloted vehicles (RPV). More recently, similar techniques have been
investigated within the context of improving learning. A major challenge of the
learning environment is that an individual's ability to perform the task, and
thus their workload experienced during the task, are constantly changing.
Cognitive Load Theory provides insight into how workload interacts with
learning. One aspect of this theory is that as information is learned it
reduces working memory demands. This paper discusses results from an RPV
training study investigating the effects of workload and learning on pupil
diameter. Specifically, pupil diameter decreased overtime as the task
difficulty was held constant, and increased as new information was presented.
The results of these studies are discussed in terms of how they can be used in
a physiologically driven adaptive training system. Keywords: Augmented Cognition; Pupil Diameter; Training; Workload | |||
| A Hierarchical Adaptation Framework for Adaptive Training Systems | | BIBAK | Full-Text | 413-421 | |
| Sven Fuchs; Angela Carpenter; Meredith Carroll; Kelly S. Hale | |||
| Real-time adaptation is challenging in both operational and training
environments, as the system must be able to identify what, why, and when
mitigation is needed, and how best to mitigate to optimize the human-system
interaction. Training systems have additional complexities, as the sole goal is
not to optimize performance as in operational environments, but to optimize
training, which may involve more error allowance for learning opportunities.
This paper outlines a proposed hierarchical adaptation framework for adaptive
training systems, involving diagnoses of learning state, performance, and
expertise. It will also discuss candidate approaches to obtaining the necessary
measurements using physiological and neurophysiological processes, provide some
guidance for designing strategies for optimal adaptation, and highlight current
challenges and future research areas. Keywords: Adaptive Training; Augmented Cognition; Training Systems | |||
| Developing and Automating a Prototype for Assessing Levels of Student Involvement | | BIBAK | Full-Text | 422-431 | |
| Curtis S. Ikehara; Martha E. Crosby | |||
| The proposed project objective is to develop and automate a methodological
technology for objectively measuring a student's affective states, cognitive
states and levels of involvement during computer-mediated instruction. Passive
devices will record gaze activity, facial expressions and body motions while
students are doing computer mediate instruction. From these measurements, a
sensor fusion classification algorithm will be developed to provide an
automated assessment of affective states, cognitive states and levels of
involvement of the student. This automated assessment system will be validated
using student interviews and rater observations. The system will provide
detailed categorized information never before available to researchers. For the
instructor, a large class could be equipped and assessed in real-time so that
an instructor can appropriately focus attention to improve the learning
environment or for student evaluation during instruction and for
self-evaluation of instructional strategies after instruction. Keywords: Cognition; real-time passive sensors; computer mediated instruction; gaze;
body motion; facial expression; affective; student involvement | |||
| Considering Cognitive Traits of University Students with Dyslexia in the Context of a Learning Management System | | BIBAK | Full-Text | 432-441 | |
| Carolina Mejía; Alicia Díaz; Juan E. Jiménez; Ramón Fabregat | |||
| This paper studies the cognitive processes involved in reading among
Spanish-speaking university students with dyslexia, and proposes to evaluate
these processes to identify specific cognitive traits. On this basis, an
automated battery for the assessment of cognitive processes was designed to be
included in a learning management system (LMS). To integrate this battery into
the LMS, a web service architecture that works independently of the LMS was
designed. The assessment battery has been built based on a multimodal
communication mechanism that delivers evaluation tasks using the visual,
auditory, and speech communication channels of human-computer interaction. Keywords: Dyslexia; cognitive traits; user model; university students; multimodal
communication | |||
| Improving Students' Meta-cognitive Skills within Intelligent Educational Systems: A Review | | BIBAK | Full-Text | 442-451 | |
| Alejandro Peña Ayala; Michiko Kayashima; Riichiro Mizoguchi; Rafael Dominguez de Leon | |||
| Metacognition aims at monitoring and regulating one's thinking devoted to
problem-solving processes and learning habits among others cognitive tasks.
Hence, individuals engaged in better acquisition of domain knowledge achieve
higher scores when they are bewaring of how to exploit their metacognitive
faculties. Thus, we present a review of some models and methods with the
purpose to understand what metacognition is and know how stimulate
metacognitive skills. In addition, we propose a Metacognition-Driven Learning
paradigm as a reference to guide the design of Intelligent Educational Systems
oriented to improve students' metacognitive skills. Keywords: Metacognition; metacognitive skills; metacognitive models;
Metacognition-Driven Learning; Intelligent Educational Systems | |||
| Interactive Neuro-Educational Technologies (I-NET): Development of a Novel Platform for Neurogaming | | BIBAK | Full-Text | 452-461 | |
| Giby Raphael; Adrienne Behneman; Veasna Tan; Nicholas Pojman; Chris Berka | |||
| The advances in sophisticated, immersive and highly engaging video gaming
technology have resulted in the introduction of "serious gaming" as platforms
for training. A virtual environment that mimics reality as closely as possible
is an effective instructional medium and also serves as a performance
improvement/evaluation platform. However, the current methodologies suffer from
several limitations: 1) conventional qualitative evaluation techniques that are
removed from the trainee's actual experience in both time and context 2) open
loop platforms fail to support adaptive training and scenarios or leverage
repeatability to accelerate training 3) failure to adapt to individual's
current psychophysiological state, limiting skill acquisition rates 4)
multi-person tasks that lack tools for objective assessment and prediction of
team cohesion or performance. As part of our initiative to invent a suite of
Interactive Neuro-Educational Technologies (I-NET), we have developed a
Neurogaming platform that will help resolve many of these limitations. Keywords: EEG; Neuroergonomics; Neurosensing; Augmented Cognition | |||
| Learning in Virtual Worlds: A New Path for Supporting Cognitive Impaired Children | | BIBAK | Full-Text | 462-471 | |
| Laura Anna Ripamonti; Dario Maggiorini | |||
| We have adopted the serious game perspective to design, develop, and test a
prototypal application, in a virtual world, aimed at teaching children affected
by Down Syndrome how to read a clock. The main idea has been to offer them a
new and intriguing learning environment to reduce the sense of frustration they
often are burdened with during educational activities. In particular, an
approach based on serious gaming has been coupled with the Feuerstein's method,
which is currently spreading as an effective support to teaching activities
aimed at impaired kids. The prototype has been developed adopting a playcentric
process and has been tested with a group of children who were unable to read
the time. Keywords: serious games; videogames; healthcare; virtual world; usability; augmented
cognition; Down Syndrome | |||
| A Longitudinal Study of P300 Brain-Computer Interface and Progression of Amyotrophic Lateral Sclerosis | | BIBAK | Full-Text | 475-483 | |
| Nathan A. Gates; Christopher K. Hauser; Eric W. Sellers | |||
| BCI can provide communication for people locked in by amyotrophic lateral
sclerosis (ALS). Empirical examination of how disease progression affects
brain-computer interface (BCI) performance has not been investigated. This
pilot study uses a longitudinal design to investigate changes in P300-BCI use
as ALS disability increases. We aimed to (a) examine the relationship between
BCI accuracy and the ALS/Functional Rating Scale and (b) examine changes in the
event-related potential (ERP) components across time. Eight subjects have been
enrolled in the study. BCI accuracy was measured and ERP components were
assessed by a principal component analysis (PCA). Two subjects have been
followed for an average of nine-months, and BCI accuracy is 99.6%. While many
research obstacles remain, these preliminary data help elucidate the
relationship between BCI performance and disease progression. Keywords: Amyotrophic lateral sclerosis; electroencephalogram; brain-computer
interface; P300 event-related potential; assistive communication | |||
| Discovering Context: Classifying Tweets through a Semantic Transform Based on Wikipedia | | BIBAK | Full-Text | 484-492 | |
| Yegin Genc; Yasuaki Sakamoto; Jeffrey V. Nickerson | |||
| By mapping messages into a large context, we can compute the distances
between them, and then classify them. We test this conjecture on Twitter
messages: Messages are mapped onto their most similar Wikipedia pages, and the
distances between pages are used as a proxy for the distances between messages.
This technique yields more accurate classification of a set of Twitter messages
than alternative techniques using string edit distance and latent semantic
analysis. Keywords: Text classification; Wikipedia; semantics; context; cognition; latent
semantic analysis | |||
| Toward a Wearable, Neurally-Enhanced Augmented Reality System | | BIBAK | Full-Text | 493-499 | |
| David H. Goldberg; R. Jacob Vogelstein; Diego A. Socolinsky; Lawrence B. Wolff | |||
| Augmented reality systems hold great promise, but as they become more
complex they can become more challenging to use. Incorporating neural
interfaces into augmented reality systems can dramatically increase usability
and utility. We explore these issues in the context of Equinox Corporation's
Night REAPER™ system-an augmented reality system for dismounted
warfighters. We describe the current Night REAPER system and then survey some
of the potential enhancements and unique design challenges associated with the
addition of a neural interface. Signals, sensors, and decoding techniques for
the system's brain-machine interface are discussed. Keywords: augmented reality; brain-machine interface; wearable systems | |||
| Interface Design Challenge for Brain-Computer Interaction | | BIBAK | Full-Text | 500-506 | |
| Jeremy Hill; Peter Brunner; Theresa M. Vaughan | |||
| Great things can be achieved even with very low bandwidth. Stephen Hawking
has been able to break new ground in theoretical physics just by twitching his
hand and cheek. Jean-Dominique Bauby was able to write a best-selling memoir by
blinking one eyelid. By reading and decoding "brain-waves", the field of
brain-computer interfacing (BCI) is poised to open up the possibility of such
expression, even for people who can no longer move a single muscle. A BCI still
requires an HCI front-end to be of practical use, but many currently-used HCIs
do not adequately address limitations on the typical target user's input (e.g.,
limited eye movement leading to poor spatial vision) or output (e.g. variable
delays, and false positives/negatives, in "pressing the button"). In this
symposium, BCI experts will present their view of the challenges arising from
these limitations. The HCI community is invited to participate in a competition
to provide the best solutions. Keywords: brain-computer interfacing (BCI); electroencephalography (EEG);
human-computer interaction (HCI); human factors; spelling; augmentative and
alternative communication (AAC); assistive technology; competition | |||
| Trust in Human-Computer Interactions as Measured by Frustration, Surprise, and Workload | | BIBAK | Full-Text | 507-516 | |
| Leanne M. Hirshfield; Stuart H. Hirshfield; Samuel Hincks; Matthew Russell; Rachel Ward; Tom Williams | |||
| We describe preliminary research that attempts to quantify the level of
trust that exists in typical interactions between human users and their
computer systems. We describe the cognitive and emotional states that are
correlated to trust, and we present preliminary experiments using functional
near infrared spectroscopy (fNIRS) and electroencephalography (EEG) to measure
these user states. Our long term goal is to run experiments that manipulate
users' level of trust in their interactions with the computer and to measure
these effects via non-invasive brain measurement. Keywords: fNIRS; EEG; electroencephalograph; near-infrared spectroscopy; workload;
frustration; surprise; trust | |||
| Idea Visibility, Information Diversity, and Idea Integration in Electronic Brainstorming | | BIBAK | Full-Text | 517-524 | |
| Elahe Javadi; Wai-Tat Fu | |||
| Despite the pervasive use of electronic media for idea generation and idea
sharing, the extent and quality of idea integration and use is relatively
understudied. Idea integration and use depends on information saliency but
little is known about how idea integration may be facilitated by user interface
features that influence information saliency. This paper examines the effect of
idea visibility on idea integration and how that relationship is moderated by
information diversity. Our laboratory experiment showed that although the basic
level of idea integration, i.e. mere reference to partners' ideas increased
when visibility increased, higher levels of idea integration decreased as
visibility increased. Information diversity was found to be a significant
moderator of the relationship between visibility and idea integration. Keywords: Idea integration; visibility; information diversity; brainstorming | |||
| The Challenges of Using Scalp-EEG Input Signals for Continuous Device Control | | BIBA | Full-Text | 525-527 | |
| Garett D. Johnson; Nicholas Waytowich; Dean J. Krusienski | |||
| Whether aiming to control a computer cursor, a robotic arm, or a wheelchair, it remains a significant challenge to achieve responsive and reliable asynchronous control via EEG signals. The most promising scalp-recorded EEG signals for this task are sensorimotor rhythms and steady-state visual evoked potentials, which have both been demonstrated to be viable for continuous device operation in controlled laboratory settings. Several issues, such as handling signal nonstationarity and identifying reliable asynchronous modes of operation, must be addressed before these scalp-EEG signals can become practical for controlling devices outside of the laboratory. | |||
| Modeling Pharmacokinetics and Pharmacodynamics on a Mobile Device to Help Caffeine Users | | BIBAK | Full-Text | 528-535 | |
| Frank E. Ritter; Kuo-Chuan (Martin) Yeh | |||
| We introduce a mobile device application that displays key information about
caffeine: the pharmacokinetics (time course of drug levels) and
pharmacodynamics (the effects of caffeine level) visually on the iPhone, iPod
Touch, and iPad. This application, Caffeine Zone, is based on an existing model
of caffeine physiology using user inputs, including caffeine dose, start time,
and consumption speed. It calculates the caffeine load in a user for the next
twenty-four hours and displays it using a line chart. In addition, it shows
whether the user is currently in the "cognitive alert zone" (the range of
caffeine where a normal person might benefit most from caffeine) or the
"possible sleep zone" (the range of caffeine where sleep is presumed not
affected by caffeine level.) Understanding the pharmacokinetics and
pharmacodynamics of caffeine can help people using caffeine to improve
alertness, including in operational environments. Caffeine Zone may also help
users create a mental model of caffeine levels when the device is not
available. We argue that this app will both teach users the complex
absorption/elimination process of caffeine and help monitor users' daily
caffeine usage. The model, with additional validation, can be part of a system
that predict cognitive state of users and provide assistances in critical
conditions. Keywords: pharmacokinetics; pharmacodynamics; caffeine; mobile app; modeling | |||
| Designing Consumer Health Information Systems: What Do User-Generated Questions Tell Us? | | BIBAK | Full-Text | 536-545 | |
| Yan Zhang; Wai-Tat Fu | |||
| Searching for health information has become a prevalent activity on the web.
The information found online has a significant impact on people's decisions on
whether to seek medical care and what treatments to undergo. However, existing
studies consistently suggest that general consumers have various difficulties
in formulating search queries using existing search engines and the queries
were often not effective in retrieving personal- and situational-relevant
information. Understanding users' information needs is a gateway to designing
effective information retrieval (IR) systems. In this study, we examined the
types of information requested by users, the characteristics of consumers'
expressions of their information needs, and their expectations for results by
analyzing the questions that general users posted on Yahoo! Answers, a popular
social Q&A site. Based on the results, we proposed design recommendations
for facilitating users' ability to articulate their health information needs
and recommendations for the presentation of information in health-related IR
systems. Keywords: Consumer health informatics; information retrieval; social Q&A; health
information searching | |||
| Estimation of Cognitive Workload during Simulated Air Traffic Control Using Optical Brain Imaging Sensors | | BIBAK | Full-Text | 549-558 | |
| Hasan Ayaz; Ben Willems; Scott C. Bunce; Patricia A. Shewokis; Kurtulus Izzetoglu; Sehchang Hah; Atul Deshmukh; Banu Onaral | |||
| Deployment of portable neuroimaging technologies to operating settings could
help assess cognitive states of personnel assigned to perform critical tasks
and thus help improve efficiency and safety of human machine systems.
Functional Near Infrared Spectroscopy (fNIR) is an emerging noninvasive brain
imaging technology that relies on optical techniques to detect brain
hemodynamics within the prefrontal cortex in response to sensory, motor, or
cognitive activation. Collaborating with the FAA William J. Hughes Technical
Center, fNIR has been used to monitor twenty four certified professional
controllers as they manage realistic Air Traffic Control (ATC) scenarios under
typical and emergent conditions. We have implemented a normalization procedure
to estimate cognitive workload levels from fNIR signals during ATC by
developing linear regression models that were informed by the respective
participants' prior n-back data. This normalization can account for oxygenation
variance due to inter-personal physiological differences. Results indicate that
fNIR is sensitive task loads during ATC. Keywords: Optical Brain Imaging; Air Traffic Control; Cognitive Workload; Functional
Near Infrared Spectroscopy; fNIR | |||
| Distributed Logging and Synchronization of Physiological and Performance Measures to Support Adaptive Automation Strategies | | BIBAK | Full-Text | 559-566 | |
| Daniel Barber; Irwin Hudson | |||
| As advances in physiological sensors make them more minimally intrusive and
easier to use, there is a clear desire by researchers in the fields of
Augmented Cognition and Neuroergonomics to incorporate them as much as
possible. To best support use of multiple measures, the data from each sensor
must be accurately synchronized across all devices and tied to performance and
environment events. However, each sensor provides different sampling
frequencies, local timing information, and timing accuracy making data
synchronization in logs or real time systems difficult. In this paper, a
modular architecture is presented to address the issue of how to synchronize
data to support analysis of physiological and performance measures. Specific
design requirements are presented to ensure the ability to accurately measure
raw sensor data and compute metrics in a distributed computing environment to
support adaptive automation strategies in a research environment. Finally, an
example system is described which combines multiple minimally invasive
physiological sensors. Keywords: Adaptive Automation; Closed-Loop Training System; Data Synchronization | |||
| Augmenting Robot Behaviors Using Physiological Measures | | BIBAK | Full-Text | 567-572 | |
| Daniel Barber; Lauren Reinerman-Jones; Stephanie J. Lackey; Irwin Hudson | |||
| In recent years, advancements in Unmanned Systems have allowed Human Robot
Interaction (HRI) to transition from direct remote control to autonomous
systems capable of self-navigation. However, these new technologies do not yet
support true mixed-initiative solider-robot teaming where soldiers work with
another agent as if it were another human being. In order to achieve this goal,
researchers must explore new types of multi-modal and natural communication
strategies and methods to provide robots improved understanding of their human
counterparts' thought process. Physiological sensors are continuously becoming
more portable and affordable leading to the possibility of providing new
insight of team member state to a robot team member. However, steps need to be
taken to improve how affective and cognitive states are measured and how these
new metrics can be used to augment the decision making process for a robot team
member. This paper describes current state of the art and next steps needed for
accurate profile creation for improved human robot team performance. Keywords: Multi-Modal Communion; Implicit Communication; Human Robot Interaction;
Physiological Measures for State Measurement | |||
| Operational Neuroscience: Neuroscience Research and Tool Development to Support the Warfighter | | BIBAK | Full-Text | 573-577 | |
| Monique E. Beaudoin; Dylan Schmorrow | |||
| This paper provides a summary of the presentations presented in the
Operational Neuroscience session during Augmented Cognition International 2011
at Human Computer Interaction International 2011 in Orlando, Florida, July,
2011. Keywords: Neuroscience; military operations; warfighter support; Cognitive readiness;
Neurotechnology; hemodynamics; pharmacokinetics; brain bio-markers | |||
| Performance Measures to Enable Agent-Based Support in Demanding Circumstances | | BIBA | Full-Text | 578-587 | |
| Fiemke Both; Mark Hoogendoorn; Rianne van Lambalgen; Rogier Oorburg; Michael de Vos | |||
| In this paper, an evaluation of measurements that can be used by a personal support agent to measure the quality of human task performance is addressed. Such measurements are important in order for a support agent to give effective and personalized support during the performance of demanding tasks. Hereby, the performance quality measurement is addressed from two perspectives, namely the human's perspective as well as the task perspective. The former represents the idea the human has about the current task performance, whereas the latter measures the actual task performance compared to the goals set for the task at hand. Criteria have been identified to compare the various measurements, and an experiment has been conducted for evaluation. Based on these evaluation results, the most useful measurements are identified to be adopted within personal support agents. | |||
| Cognitive Adaptive Man Machine Interfaces for the Firefighter Commander: Design Framework and Research Methodology | | BIBAK | Full-Text | 588-597 | |
| Maurits de Graaf; Michel Varkevisser; Masja Kempen; Nicolas Jourden | |||
| The ARTEMIS CAMMI project aims at developing a joint-cognitive system to
optimise human operator's performance under demanding labour conditions. The
CAMMI domain applications concern avionics, automotive, and civil emergencies.
In this paper we address the development of a joint-cognitive system for
firefighter commanders to optimise situational and team awareness by reducing
the workload through mitigation strategies and an adaptive HMI. A general
framework and a research methodology are presented to explore the possibilities
of applying the CAMMI building blocks in the development of systems to support
the handling of firefighter emergencies. Keywords: HMI; Situational Awareness; Team Awareness; Mental Load; Mitigation
Strategies | |||
| An Intelligent Infrastructure for In-Flight Situation Awareness of Aviation Pilots | | BIBAK | Full-Text | 598-607 | |
| Alessandro G. Di Nuovo; Rosario Bruno Cannavò; Santo Di Nuovo | |||
| This paper presents an infrastructure that integrates intelligent agents in
order to monitor, in real time, the attention of aviation pilots during
training/operative flight missions. The primary goal of this infrastructure is
to make the decision process easier and increase Situation Awareness, thus to
increase flight safety pro-actively. The proposed hardware/software platform
could be able to anticipate the onset of problems which can lead to incidents,
and to make easier the decision making process toward a positive solution of
the problem. To attain the goal, a multi-agent system is designed using the
most recent technology in the field of artificial vision and of the measurement
of psychophysical parameters, starting from the most recent knowledge of visual
attention to arrive at the development of an original and innovative model of
Augmented Reality. Finally it is provided a case study based on an event
actually occurred to prove effectiveness of the proposed platform. Keywords: Situation Awareness; Intelligent Agents; Augmented Reality | |||
| Applications of Functional Near Infrared Imaging: Case Study on UAV Ground Controller | | BIBAK | Full-Text | 608-617 | |
| Kurtulus Izzetoglu; Hasan Ayaz; Justin Menda; Meltem Izzetoglu; Anna C. Merzagora; Patricia A. Shewokis; Kambiz Pourrezaei; Banu Onaral | |||
| Functional Near-Infrared (fNIR) spectroscopy is an emerging optical brain
imaging technology that enables assessment of brain activity through the intact
skull in human subjects. fNIR systems developed during the last decade allow
for a rapid, non-invasive method of measuring the brain activity of a subject
while conducting tasks in realistic environments. This paper introduces
underlying principles and various fNIR designs currently applied to real-time
settings, such as monitoring Unmanned Aerial Vehicle (UAV) operator's expertise
development and cognitive workload during simulated missions. Keywords: Near-infrared spectroscopy; optical brain imaging; fNIR; human performance
assessment | |||
| Augmented Phonocardiogram Acquisition and Analysis | | BIBA | Full-Text | 618-627 | |
| Nancy E. Reed; Todd R. Reed | |||
| Heart auscultation (the interpretation of heart sounds by a physician) is a widely used screening method for heart disease. It is well documented, however, that with the exception of expert cardiologists, physicians' auscultation skills are limited. It has also been shown that standard training methods do little to improve these skills. In this paper, we propose an architecture for a phonocardiogram analysis system that can augment a physician's auscultation abilities and serve as a training aid to improve those abilities. | |||
| Today's Competitive Objective: Augmenting Human Performance | | BIBAK | Full-Text | 628-635 | |
| Kay M. Stanney; Kelly S. Hale | |||
| Gaining competitive advantage requires acquiring or developing a capability
that allows an organization or individual to outperform its competitors. In
today's technology-driven environment, where human capabilities are struggling
to keep up with technology offerings, techniques for augmenting human
performance are becoming the critical gap that is precluding realizing the full
benefits that these technology advances have to offer. The challenge is thus to
develop tools and techniques that augment the human potential in order to best
couple it to advancing complex interactive systems. In this void, those who are
developing the capability to support real-time measurement, diagnosis, and
augmentation of human performance may be the first to gain the competitive
edge. Keywords: Augmented cognition; Adaptive systems; human performance | |||
| Measuring the Effectiveness of Stress Prevention Programs in Military Personnel | | BIBAK | Full-Text | 636-646 | |
| Andrea H. Taylor; Sae Lynne Schatz | |||
| The effects of stress on military personnel are a pervasive concern. To
mitigate stress's negative impacts, Defense agencies employ stress inoculation
training and, more recently, have begun to provide stress resilience
instruction. However, such pre-deployment programs suffer from measurement
limitations, rendering their assessment difficult. Novel application of
objective, individual, repeated measures, conducted under realistically
stressful settings, may help address this gap. Towards that end, we reviewed
common neurophysiological techniques and examined their usefulness for
measuring stress reactions. These techniques include: 1) cortisol in the blood
or saliva, 2) adrenaline in the blood or urine, 3) skin conductivity, 4) EEG,
5) Skin conductance, and 6) Heart rate. Keywords: Stress; Training; Resilience; Inoculation; Physiological Measurement | |||
| Adaptive Attention Allocation Support: Effects of System Conservativeness and Human Competence | | BIBA | Full-Text | 647-656 | |
| Peter-Paul van Maanen; Teun Lucassen; Kees van Dongen | |||
| Naval tactical picture compilation is a task for which allocation of attention to the right information at the right time is crucial. Performance on this task can be improved if a support system assists the human operator. However, there is evidence that benefits of support systems are highly dependent upon the systems' tendency to support. This paper presents a study into the effects of different levels of support conservativeness (i.e., tendency to support) and human competence on performance and on the human's trust in the support system. Three types of support are distinguished: fixed, liberal and conservative support. In fixed support, the system calculates an estimated optimal decision and suggests this to the human. In the liberal and conservative support types, the system estimated the important information in the problem space in order to make a correct decision and directs the human's attention to this information. In liberal support, the system attempts to direct the human's attention using only the assessed task requirements, whereas in conservative support, the this attempt is done provided that it has been estimated that the human is not already paying attention (more conservative). Overall results do not confirm our hypothesis that adaptive conservative support leads to the best performances. Furthermore, especially high-competent humans showed more trust in a system when delivered support was adapted to their specific needs. | |||
| A Dynamic Approach to the Physiological-Based Assessment of Resilience to Stressful Conditions | | BIBAK | Full-Text | 657-666 | |
| Mikhail Zotov; Chris Forsythe; Alexey Voyt; Inga Akhmedova; Vladimir Petrukovich | |||
| In the presented research, a new algorithm of detection and analysis of
non-stationary phases (NSPh), characterizing sudden changes in heart rate
variability (HRV) parameters was used. Physiological reactions of air traffic
controllers during the performance of training scenario were estimated. 39
participants -- 14 experienced air traffic controllers and 25 students
performed a 40-minute scenario, which included 3 stressful incidents: a rapid
increase in air traffic density, low fuel level and plane engine failure.
Students also performed the scenario after brief training. The results have
shown that as expertise grows respondents show a significant decrease in
duration and change in patterns of non-stationary phases of heart rate arising
in response to the stressful incidents. These changes of parameters of
non-stationary phases are connected with increased efficiency of air traffic
controllers' cognitive performance in stressful conditions. The research has
illustrated that the analysis of non-stationary phase parameters complements
classical HRV measures and may be used for assessment of physiological
responses of operators in Augmented Cognition applications. Keywords: heart rate variability; cognitive workload; simulation-based training Note: Best Paper Award | |||