This study investigated the neural correlates of flow states using fMRI. It aimed to test predictions from synchronization theory that flow involves increased activation in attention and reward networks compared to boredom and frustration states. Participants completed tasks designed to induce each state while in the scanner. Preliminary results from one participant found greater activation in attention-related areas like the inferior parietal lobe and reward-related areas like the thalamus during flow vs boredom. Flow vs frustration activated visual cortex areas but no clear reward areas. Further research is needed to fully test the synchronization component of the theory and address limitations like task modality differences.
This document summarizes an article that appeared in a journal published by Elsevier. The article examines differences in brain activation patterns between schizophrenia patients and healthy controls during a simple target detection task using fMRI. The key findings were that schizophrenia patients failed to deactivate default mode network regions like the posterior cingulate cortex during the task, and they activated the dorsal attention network rather than the executive network that healthy controls activated. These results support theories of dysfunctional recruitment of large-scale brain networks in schizophrenia.
This document outlines a lecture on neuroeconomics and the multiple systems hypothesis given by David Laibson at Harvard University. It defines neuroeconomics as the study of biological foundations of economic cognition, like brain systems and neurotransmitters. The lecture discusses the multiple systems hypothesis, which proposes that the brain integrates signals from multiple systems that process information qualitatively differently and differentially weight attributes like time delay. Systems discussed include an affective system associated with mesolimbic dopamine that is fast, unconscious, and myopic versus an analytic system in the prefrontal cortex that is slow, conscious, and forward-looking. Predictions from this hypothesis and supporting evidence from studies manipulating cognitive load, willpower, affect, and more are outlined
This document discusses issues with reproducibility in EEG research and proposes solutions. It notes that flexible choices in EEG methodology and exploratory analyses can lead to false positives. Simulations demonstrate how double dipping, multiple comparisons, and lack of independent replication can produce significant effects from noise alone. The document advocates for preregistering analysis plans, including dummy effects in studies, subdividing data for exploration and replication, and using registered reports to improve reproducibility in EEG research.
This study examined functional connectivity of the medial temporal lobe (MTL) and its relation to learning and awareness. Participants completed a sensory learning task and were classified as AWARE or UNAWARE based on their ability to learn tone-visual stimulus associations. For AWARE participants, MTL activity correlated with learned discrimination and reversal, engaging dorsolateral prefrontal and occipital cortices. For UNAWARE participants, MTL activity correlated only with simple facilitation and engaged contralateral MTL, thalamus regions. This suggests the MTL contribution to learning depends on its pattern of interactions with other brain regions.
The document discusses approaches for modern disease surveillance using collaboration and semantic web technologies. It describes how tools like InSTEDD Evolve use machine learning, social media, and geospatial data to improve early detection of disease outbreaks and facilitate effective coordination of public health responses. Key components of the proposed approach include automated analysis, user feedback loops, and representation of unstructured data to enable early detection and verification of health-related events.
The document provides guidelines for successful conference abstracts, noting that high-rated abstracts discuss topics of current interest to the field, clearly define a novel problem and proposed solution, and use current terminology, while low-rated abstracts lack these elements. It also provides tips for writing an abstract such as including background, methods, results and conclusions sections as well as ensuring the topic, work, and context are captured clearly in the title. The document aims to help authors develop abstracts that will be viewed positively by reviewers.
Here are the responses to the questions:
1. A statistical population is the entire set of individuals or objects of interest. A sample is a subset of the population selected to represent the population. The sample infers information about the characteristics, attributes, and properties of the entire population.
2. Variance is the average of the squared deviations from the mean. It is calculated as the sum of the squared deviations from the mean divided by the number of values in the data set minus 1. Standard deviation is the square root of the variance. It measures how far data values spread out from the mean.
3. No data was provided to create graphs. Additional data on the number of fish in each age group would be needed.
Spatial and Temporal Features of Noise in fMRIVanessa S
This document summarizes work on developing a method to distinguish noise from networks in fMRI data using spatial and temporal features. The method involves preprocessing fMRI data, performing independent component analysis to extract components, defining 135 spatial and 111 temporal features of the components, manually labeling a standard set to identify component types (e.g. noise, eyeballs, head motion), and using machine learning with the features to automatically predict component types in other datasets with good accuracy. Evaluation on new datasets could demonstrate the utility of the method for automatic filtration of noisy components in large fMRI databases.
This document summarizes an article that appeared in a journal published by Elsevier. The article examines differences in brain activation patterns between schizophrenia patients and healthy controls during a simple target detection task using fMRI. The key findings were that schizophrenia patients failed to deactivate default mode network regions like the posterior cingulate cortex during the task, and they activated the dorsal attention network rather than the executive network that healthy controls activated. These results support theories of dysfunctional recruitment of large-scale brain networks in schizophrenia.
This document outlines a lecture on neuroeconomics and the multiple systems hypothesis given by David Laibson at Harvard University. It defines neuroeconomics as the study of biological foundations of economic cognition, like brain systems and neurotransmitters. The lecture discusses the multiple systems hypothesis, which proposes that the brain integrates signals from multiple systems that process information qualitatively differently and differentially weight attributes like time delay. Systems discussed include an affective system associated with mesolimbic dopamine that is fast, unconscious, and myopic versus an analytic system in the prefrontal cortex that is slow, conscious, and forward-looking. Predictions from this hypothesis and supporting evidence from studies manipulating cognitive load, willpower, affect, and more are outlined
This document discusses issues with reproducibility in EEG research and proposes solutions. It notes that flexible choices in EEG methodology and exploratory analyses can lead to false positives. Simulations demonstrate how double dipping, multiple comparisons, and lack of independent replication can produce significant effects from noise alone. The document advocates for preregistering analysis plans, including dummy effects in studies, subdividing data for exploration and replication, and using registered reports to improve reproducibility in EEG research.
This study examined functional connectivity of the medial temporal lobe (MTL) and its relation to learning and awareness. Participants completed a sensory learning task and were classified as AWARE or UNAWARE based on their ability to learn tone-visual stimulus associations. For AWARE participants, MTL activity correlated with learned discrimination and reversal, engaging dorsolateral prefrontal and occipital cortices. For UNAWARE participants, MTL activity correlated only with simple facilitation and engaged contralateral MTL, thalamus regions. This suggests the MTL contribution to learning depends on its pattern of interactions with other brain regions.
The document discusses approaches for modern disease surveillance using collaboration and semantic web technologies. It describes how tools like InSTEDD Evolve use machine learning, social media, and geospatial data to improve early detection of disease outbreaks and facilitate effective coordination of public health responses. Key components of the proposed approach include automated analysis, user feedback loops, and representation of unstructured data to enable early detection and verification of health-related events.
The document provides guidelines for successful conference abstracts, noting that high-rated abstracts discuss topics of current interest to the field, clearly define a novel problem and proposed solution, and use current terminology, while low-rated abstracts lack these elements. It also provides tips for writing an abstract such as including background, methods, results and conclusions sections as well as ensuring the topic, work, and context are captured clearly in the title. The document aims to help authors develop abstracts that will be viewed positively by reviewers.
Here are the responses to the questions:
1. A statistical population is the entire set of individuals or objects of interest. A sample is a subset of the population selected to represent the population. The sample infers information about the characteristics, attributes, and properties of the entire population.
2. Variance is the average of the squared deviations from the mean. It is calculated as the sum of the squared deviations from the mean divided by the number of values in the data set minus 1. Standard deviation is the square root of the variance. It measures how far data values spread out from the mean.
3. No data was provided to create graphs. Additional data on the number of fish in each age group would be needed.
Spatial and Temporal Features of Noise in fMRIVanessa S
This document summarizes work on developing a method to distinguish noise from networks in fMRI data using spatial and temporal features. The method involves preprocessing fMRI data, performing independent component analysis to extract components, defining 135 spatial and 111 temporal features of the components, manually labeling a standard set to identify component types (e.g. noise, eyeballs, head motion), and using machine learning with the features to automatically predict component types in other datasets with good accuracy. Evaluation on new datasets could demonstrate the utility of the method for automatic filtration of noisy components in large fMRI databases.
This document summarizes a study that investigated emotion recognition from physiological data using different classifiers and setups. Physiological signals were collected from subjects watching videos and their emotional states were recorded. Features were extracted from the signals and classified using models like random forests. Subject-based and trial-based cross-validation was used to evaluate the impact of personalization. The results showed the classifiers performed best in a personalized model that grouped similar subjects, achieving enhanced emotional state prediction from physiological data without additional feedback.
How to measure and improve brain-based outcomes that matter in health careSharpBrains
Pioneers advancing health research, prevention and treatment will help us understand emerging best practices where targeted assessments, monitoring and interventions can transfer into significant healthcare and quality of life outcomes.
-- Chair: Alvaro Fernandez, CEO & Co-Founder of SharpBrains
-- Dr. Madeleine S Goodkind, staff psychologist at New Mexico VA Health Care System
-- Dr. Randy McIntosh, Vice-president of Research and Director of Baycrest’s Rotman Research Institute
-- Chris Berka, CEO and Co-Founder of Advanced Brain Monitoring (ABM)
Presentation @ The 2015 SharpBrains Virtual Summit http://sharpbrains.com/summit-2015/agenda
Analogy, Causality, and Discovery in Science: The engines of human thoughtCITE
13 January 2015, Tuesday
12:45 pm – 2:00 pm
has been changed to RMS 101, Runme Shaw Bldg., HKU
By Professor Kevin Niall DUNBAR,
College of Education, University of Maryland, College Park, US
http://sol.edu.hku.hk/analogy-causality-discovery-science-engines-human-thought/
Ultrasound Stimulation for Peripheral Nerve Repair v7Emily Ashbolt
Ultrasound stimulation increases neurite branching and outgrowth in peripheral neurons. Higher intensity ultrasound led to greater neurite branching and total outgrowth compared to lower intensities and untreated controls. Ultrasound also increased the metabolic activity of Schwann cells, peripheral glial cells that enhance neurite outgrowth. These findings suggest ultrasound may promote peripheral nerve regeneration by stimulating neuronal and glial responses. Further study is needed to understand the cellular mechanisms and potential for ultrasound as a non-invasive therapy for peripheral nerve injuries.
ICCSS2015 talk: Null model for meme popularityJames Gleeson
The document presents a model of how memes compete for popularity when spreading over social networks. The model accounts for the effects of human memory timescales and network structure on meme diffusion. It shows that competition between memes for limited user attention can induce critical behavior, producing power law popularity distributions and linear popularity growth over time. Comparison to empirical data demonstrates the model provides a useful null model for understanding how memory, networks and competition influence meme popularity.
The document summarizes a study that investigated whether auditory attention is necessary for the cortical propagation of binaural beats. The study found that binaural beats were detected at the proposed brain location even with a distractor task, indicating the signal propagation is independent of attentional control. This suggests binaural beats could be used for applications like relaxation or hypnosis without requiring attention.
Predicting Contradiction Intensity: Low, Strong or Very Strong?Ismail BADACHE
Reviews on web resources (e.g. courses, movies) become increasingly exploited in text analysis tasks (e.g. opinion detection, controversy detection). This paper investigates contradiction intensity in reviews exploiting different features such as variation of ratings and variation of polarities around specific entities (e.g. aspects, topics). Firstly, aspects are identified according to the distributions of the emotional terms in the vicinity of the most frequent nouns in the reviews collection. Secondly, the polarity of each review segment containing an aspect is estimated. Only resources containing these aspects with opposite polarities are considered. Finally, some features are evaluated, using feature selection algorithms, to determine their impact on the effectiveness of contradiction intensity detection. The selected features are used to learn some state-of-the-art learning approaches. The experiments are conducted on the Massive Open Online Courses data set containing 2244 courses and their 73,873 reviews, collected from coursera.org. Results showed that variation of ratings, variation of polarities, and reviews quantity are the best predictors of contradiction intensity. Also, J48 was the most effective learning approach for this type of classification.
Computational methods have complemented experimental and clinical neurosciences and led to improvements in our understanding of the nervous systems in health and disease. In parallel, neuromodulation in form of electrical and magnetic stimulation is gaining increasing acceptance in chronic and intractable diseases. First, we will present models of slow dynamics emerging on large cortical scales controlled by both subcortical networks and neurovascular coupling. The focus is on modeling migraine, though this approach is nested within the wider interest in modeling slow and large-scale dynamics in the brain. The aim is not only to better understand pain conditions and fluctuations in the resting state that causes these conditions but also to identify new opportunities to intervene with medical devices and implantable neuroprostheses. To this end, we then present the relevant state of the art of neuromodulation in migraine and approaches in fusion of both developments towards a translational computational neuroscience.
Search process as transitions between neural statesyasharmoshfeghi
Search is one of the most performed activities on the World Wide Web. Various conceptual models postulate that the search process can be broken down into distinct emotional and cognitive states of searchers while they engage in a search process. These models significantly contribute to our understanding of the search process. However, they are typically based on self-report measures, such as surveys, questionnaire, etc. and therefore, only indirectly monitor the brain activity that supports such a process. With this work, we take one step further and directly measure the brain activity involved in a search process. To do so, we break down a search process into five time periods: a realisation of Information Need, Query Formulation, Query Submission, Relevance Judgment and Satisfaction Judgment. We then investigate the brain activity between these time periods. Using functional Magnetic Resonance Imaging (fMRI), we monitored the brain activity of twenty-four participants during a search process that involved answering questions carefully selected from the TREC-8 and TREC 2001 Q/A Tracks. This novel analysis that focuses on transitions rather than states reveals the contrasting brain activity between time periods -- which enables the identification of the distinct parts of the search process as the user moves through them.This work, therefore, provides an important first step in representing the search process based on the transitions between neural states. Discovering more precisely how brain activity relates to different parts of the search process will enable the development of brain-computer interactions that better support search and search interactions, which we believe our study and conclusions advance.
Jorge Alberto Costa e Silva-Psiquiatría: situación actual y perspectivas de f...Fundación Ramón Areces
'Psiquiatría: situación actual y perspectivas de futuro'. Este es el título del simposio internacional que organizamos el 20 de junio de 2016 en la Fundación Ramón Areces con las fundaciones Juan José López-Ibor y Lilly en homenaje al doctor Juan José López-Ibor, fallecido en enero de 2015. Durante esta jornada, expertos internacionales abordaron la profunda crisis que atraviesa la psiquiatría como disciplina científica y especialidad médica. Además, se presentó el libro con el mismo título del simposio, también en recuerdo del doctor López-Ibor.
Panel Discussion at the Building Research Collaborations retreat, Aug. 23, 2012
Panelists were Julie Honaker, Namas Chandra, Fred Luthans, Debra Hope, Scott Stoltenberg, Mario Scalora and Timothy Carr
A Wearable Accelerometer System for Unobtrusive Monitoring of Parkinson’s Dis...Michael J. Montgomery
Abstract: Parkinson’s disease is a complex condition currently monitored at home with paper diaries which rely on subjective and unreliable assessment of motor function at nonstandard time intervals. We present an innovative wearable and unobtrusive monitoring system for patients which can help provide physicians with significantly improved assessment of patients’ responses to drug therapies and lead to better-targeted treatment regimens. In this paper we describe the algorithmic development of the system and an evaluation in patients for assessing the onset and duration of advanced PD motor symptoms.
A Mindful Way to Staying Mentally Healthy at UniversityBarry Tse
A deck prepared for an online talk given to the University of Liverpool students and staff in Feb 2022 Feel Good Month. The talk touched on common psychological issues identified in a recent study in the UK and explained some of the problems that plagued our modern lifestyle. Secular mindfulness is then introduced as a tool to regain control of our declining ability to focus and our stress response that has constantly been put on hyperdrive due to our evolution, neurological wiring, and psychological processes needed for our survival.
The document reports on a study that examined the relationship between general well-being and everyday memory. The study hypothesized that individuals with greater general well-being would have better everyday memory. 99 participants completed questionnaires measuring general well-being and everyday memory. A significant negative correlation was found, supporting the hypothesis that better general well-being is associated with better everyday memory. However, the study had limitations such as a small sample size and using self-report measures. Future research could explore this relationship further with a larger, more diverse sample.
Three hybrid classifiers for the detection of emotions in suicide notesJee-Hyub Kim
Suicides increasingly present a major concern in today's society. We describe our system for the recognition of emotions in suicide notes. Motivated by the sparse and imbalanced data as well as the complex annotation scheme, we have considered three hybrid approaches for distinguishing between the different categories. Each of the three approaches combines machine learning with manually derived rules, where the latter target very sparse emotion categories. The first approach considers the task as single label multi-class classification, where an SVM and a CRF classifier are trained to recognise fifteen different categories and their results are combined. Our second approach trains individual binary classifiers (SVM and CRF) for each of the fifteen sentence categories and returns the union of the classifiers as the final result. Finally, our third approach is a combination of binary and multi-class classifiers (SVM and CRF) trained on different subsets of the training data. We considered a number of different feature configurations. All three systems were tested on 300 unseen messages. Our second system had the best performance of the three,yielding an F1 score of 45.6% and a Precision of 60.1% whereas the best Recall (43.6%) was obtained using the third system.
Dr. Frederick Starr is a psychiatrist and pioneer in the field of neurotechnology. He founded Myneurva to advance neurofeedback treatment. Neurofeedback uses EEG to monitor brain activity and provide feedback to change brainwaves. It has been shown to effectively treat conditions like PTSD, ADHD, anxiety, depression, autism, and more. Dr. Starr's lecture discussed what neurofeedback is, how it works, the research supporting its use for various mental and physical health conditions, and the Starrbase system for remote neurofeedback treatment and diagnosis using QEEG brain mapping and artificial intelligence.
This document discusses key concepts in statistics including descriptive and inferential statistics, populations and samples, variables, and methods of collecting and presenting data. Specifically, it defines statistics, the two main types (descriptive and inferential), populations as all elements studied and samples as subsets of populations. It also outlines common variable types, methods of collecting data, different sampling techniques, how to construct frequency distributions and cumulative frequency distributions for qualitative and quantitative variables, and how to present data using bar charts and histograms.
O R I G I N A L P A P E RKnut W. Sørgaard Æ Peter Ryan Æ R.docxhopeaustin33688
O R I G I N A L P A P E R
Knut W. Sørgaard Æ Peter Ryan Æ Robert Hill Æ Ian Dawson and the OSCAR group
Sources of stress and burnout in acute psychiatric care:
inpatient vs. community staff
Received: 23 November 2006 / Accepted: 11 June 2007 / Published online: 13 August 2007
j Abstract Background Professionals who work
alone or in small teams often provide services for
people with serious mental health problems in com-
munity settings. Stress is common in community
teams and this may cause burnout and threaten the
quality and stability of the services. This study com-
pares levels of burnout and sources of stress among
community and acute ward staff in six European
centres. Methods A total of 6 acute ward (N = 204)
and community staff (N = 209) in 5 different Euro-
pean countries filled out the Maslach Burnout
Inventory (MBI), the Mental Health Professional
Scale (MHPSS) the Agervold Questionnaire for psy-
chosocial work environment (QPWES) in addition
to a comprehensive demographic questionnaire.
Results In the univariate analyses, except for Emo-
tional Exhaustion (MBI), there were no differences in
burnout between the two groups of staff. Community
teams reported more organisational problems, higher
work demands, less contact with colleagues, but also
better social relations and more control over their
work. The ward staff was more satisfied with the or-
ganisational structure and access to colleagues, but
complained about lack of control over operating
conditions at work. The multivariate analyses identi-
fied four groups of staff: (1) a Control-dissatisfied and
Contact satisfied group (N = 184) with 2/3 coming
from the wards. (2) A Contact-satisfied and Work-
demand dissatisfied group (N = 147) with 3=4 from
the community staff. (3) A Control- and Contact
dissatisfied group (N = 47) with a majority from
community teams, and (4) a Contact- and Work de-
mand satisfied group (N = 37) with a majority from
the wards. Conclusion Burnout as measured was not a
serious problem among community and ward staff
members, and did not differentiate between the two
groups. Acute ward working implied lack of control
but much contact with colleagues, whereas commu-
nity work entailed more control but demanding work
in terms of difficult task and hard-to-find-solutions.
j Key words stress – burnout – community care –
acute wards
Introduction
Professionals who often work alone or in small teams
are increasingly providing the care of people with
serious mental health problems in community set-
tings. Continuous structural changes in mental health
systems, with accompanying changes in role
requirements, exposes mental health professionals to
new sources of stress. Studies show that community
mental health staff experience considerable stress [6,
11, 20, 22] and that community work is more stressful
than working in a ward [5, 23]. Concerns have been
raised that such high levels of stress may cause de-
moralisation and burnout and thus threaten the
qual.
This document provides an overview of cognitive psychology and models of memory. It summarizes the multi-store model which includes sensory memory, short-term memory, and long-term memory. Evidence is presented for the capacity, encoding, and duration of short-term memory based on the research of Miller, Baddeley, and Peterson & Peterson. The working memory model is also summarized. Finally, applications to eyewitness testimony and memory improvement strategies are briefly discussed.
Visual Analytics for Healthcare - Panel at AMIA 2012 in ChicagoAdam Perer
AMIA 2012 Panel on Visual Analytics for Healthcare
Organizer:
Adam Perer, PhD
Research Scientist
IBM T.J. Watson Research Center, Hawthorne, NY
Panelists:
Ben Shneiderman, PhD
Professor, Computer Science
University of Maryland, College Park, MD
Yuval Shahar, PhD
Professor, Head of the Medical Informatics Research Center
Ben Gurion University, Beer Sheva, Israel
Jeffrey Heer, PhD
Assistant Professor, Computer Science
Stanford University, Stanford, CA
David Gotz, PhD
Research Scientist
IBM T.J. Watson Research Center, Hawthorne, NY
Abstract
With the proliferation of medical information technology, users at all levels of the healthcare system have access to more data than ever before6. This data can be of tremendous value but is often difficult to access and interpret. For example clinicians are often faced with the challenging task of analyzing large amounts of unstructured, multi-modal, and longitudinal data to effectively diagnose and monitor the progression of a patient’s disease4,5. Similarly, patients are confronted with the difficult task of understanding the trends and correlations within data related to their own health. At the institutional level, healthcare organizations are faced with the desire to use data to improve overall operational efficiency and performance, while continuing to maintain the quality of patient care and safety.
Recent advances in visualization and visual analytics have the potential to help each of the user groups listed above do more with the often overwhelming amount of data available to them 1,3,7,8. However, to be successful, visualization designers and clinicians must work together closely to ensure that the right technologies are used to help address the meaningful problems. Unfortunately, despite the continuous use of scientific visualization and visual analytics in medical applications, the lack of communication between engineers and physicians has meant that only basic visualization and analytics techniques are currently employed in clinical practice2,9.
The goal of this panel is to present state-of-the-art visualization applications for healthcare and engage the leading physicians and clinical researchers at AMIA to discuss the areas in healthcare where additional visualization techniques are most needed.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
This document summarizes a study that investigated emotion recognition from physiological data using different classifiers and setups. Physiological signals were collected from subjects watching videos and their emotional states were recorded. Features were extracted from the signals and classified using models like random forests. Subject-based and trial-based cross-validation was used to evaluate the impact of personalization. The results showed the classifiers performed best in a personalized model that grouped similar subjects, achieving enhanced emotional state prediction from physiological data without additional feedback.
How to measure and improve brain-based outcomes that matter in health careSharpBrains
Pioneers advancing health research, prevention and treatment will help us understand emerging best practices where targeted assessments, monitoring and interventions can transfer into significant healthcare and quality of life outcomes.
-- Chair: Alvaro Fernandez, CEO & Co-Founder of SharpBrains
-- Dr. Madeleine S Goodkind, staff psychologist at New Mexico VA Health Care System
-- Dr. Randy McIntosh, Vice-president of Research and Director of Baycrest’s Rotman Research Institute
-- Chris Berka, CEO and Co-Founder of Advanced Brain Monitoring (ABM)
Presentation @ The 2015 SharpBrains Virtual Summit http://sharpbrains.com/summit-2015/agenda
Analogy, Causality, and Discovery in Science: The engines of human thoughtCITE
13 January 2015, Tuesday
12:45 pm – 2:00 pm
has been changed to RMS 101, Runme Shaw Bldg., HKU
By Professor Kevin Niall DUNBAR,
College of Education, University of Maryland, College Park, US
http://sol.edu.hku.hk/analogy-causality-discovery-science-engines-human-thought/
Ultrasound Stimulation for Peripheral Nerve Repair v7Emily Ashbolt
Ultrasound stimulation increases neurite branching and outgrowth in peripheral neurons. Higher intensity ultrasound led to greater neurite branching and total outgrowth compared to lower intensities and untreated controls. Ultrasound also increased the metabolic activity of Schwann cells, peripheral glial cells that enhance neurite outgrowth. These findings suggest ultrasound may promote peripheral nerve regeneration by stimulating neuronal and glial responses. Further study is needed to understand the cellular mechanisms and potential for ultrasound as a non-invasive therapy for peripheral nerve injuries.
ICCSS2015 talk: Null model for meme popularityJames Gleeson
The document presents a model of how memes compete for popularity when spreading over social networks. The model accounts for the effects of human memory timescales and network structure on meme diffusion. It shows that competition between memes for limited user attention can induce critical behavior, producing power law popularity distributions and linear popularity growth over time. Comparison to empirical data demonstrates the model provides a useful null model for understanding how memory, networks and competition influence meme popularity.
The document summarizes a study that investigated whether auditory attention is necessary for the cortical propagation of binaural beats. The study found that binaural beats were detected at the proposed brain location even with a distractor task, indicating the signal propagation is independent of attentional control. This suggests binaural beats could be used for applications like relaxation or hypnosis without requiring attention.
Predicting Contradiction Intensity: Low, Strong or Very Strong?Ismail BADACHE
Reviews on web resources (e.g. courses, movies) become increasingly exploited in text analysis tasks (e.g. opinion detection, controversy detection). This paper investigates contradiction intensity in reviews exploiting different features such as variation of ratings and variation of polarities around specific entities (e.g. aspects, topics). Firstly, aspects are identified according to the distributions of the emotional terms in the vicinity of the most frequent nouns in the reviews collection. Secondly, the polarity of each review segment containing an aspect is estimated. Only resources containing these aspects with opposite polarities are considered. Finally, some features are evaluated, using feature selection algorithms, to determine their impact on the effectiveness of contradiction intensity detection. The selected features are used to learn some state-of-the-art learning approaches. The experiments are conducted on the Massive Open Online Courses data set containing 2244 courses and their 73,873 reviews, collected from coursera.org. Results showed that variation of ratings, variation of polarities, and reviews quantity are the best predictors of contradiction intensity. Also, J48 was the most effective learning approach for this type of classification.
Computational methods have complemented experimental and clinical neurosciences and led to improvements in our understanding of the nervous systems in health and disease. In parallel, neuromodulation in form of electrical and magnetic stimulation is gaining increasing acceptance in chronic and intractable diseases. First, we will present models of slow dynamics emerging on large cortical scales controlled by both subcortical networks and neurovascular coupling. The focus is on modeling migraine, though this approach is nested within the wider interest in modeling slow and large-scale dynamics in the brain. The aim is not only to better understand pain conditions and fluctuations in the resting state that causes these conditions but also to identify new opportunities to intervene with medical devices and implantable neuroprostheses. To this end, we then present the relevant state of the art of neuromodulation in migraine and approaches in fusion of both developments towards a translational computational neuroscience.
Search process as transitions between neural statesyasharmoshfeghi
Search is one of the most performed activities on the World Wide Web. Various conceptual models postulate that the search process can be broken down into distinct emotional and cognitive states of searchers while they engage in a search process. These models significantly contribute to our understanding of the search process. However, they are typically based on self-report measures, such as surveys, questionnaire, etc. and therefore, only indirectly monitor the brain activity that supports such a process. With this work, we take one step further and directly measure the brain activity involved in a search process. To do so, we break down a search process into five time periods: a realisation of Information Need, Query Formulation, Query Submission, Relevance Judgment and Satisfaction Judgment. We then investigate the brain activity between these time periods. Using functional Magnetic Resonance Imaging (fMRI), we monitored the brain activity of twenty-four participants during a search process that involved answering questions carefully selected from the TREC-8 and TREC 2001 Q/A Tracks. This novel analysis that focuses on transitions rather than states reveals the contrasting brain activity between time periods -- which enables the identification of the distinct parts of the search process as the user moves through them.This work, therefore, provides an important first step in representing the search process based on the transitions between neural states. Discovering more precisely how brain activity relates to different parts of the search process will enable the development of brain-computer interactions that better support search and search interactions, which we believe our study and conclusions advance.
Jorge Alberto Costa e Silva-Psiquiatría: situación actual y perspectivas de f...Fundación Ramón Areces
'Psiquiatría: situación actual y perspectivas de futuro'. Este es el título del simposio internacional que organizamos el 20 de junio de 2016 en la Fundación Ramón Areces con las fundaciones Juan José López-Ibor y Lilly en homenaje al doctor Juan José López-Ibor, fallecido en enero de 2015. Durante esta jornada, expertos internacionales abordaron la profunda crisis que atraviesa la psiquiatría como disciplina científica y especialidad médica. Además, se presentó el libro con el mismo título del simposio, también en recuerdo del doctor López-Ibor.
Panel Discussion at the Building Research Collaborations retreat, Aug. 23, 2012
Panelists were Julie Honaker, Namas Chandra, Fred Luthans, Debra Hope, Scott Stoltenberg, Mario Scalora and Timothy Carr
A Wearable Accelerometer System for Unobtrusive Monitoring of Parkinson’s Dis...Michael J. Montgomery
Abstract: Parkinson’s disease is a complex condition currently monitored at home with paper diaries which rely on subjective and unreliable assessment of motor function at nonstandard time intervals. We present an innovative wearable and unobtrusive monitoring system for patients which can help provide physicians with significantly improved assessment of patients’ responses to drug therapies and lead to better-targeted treatment regimens. In this paper we describe the algorithmic development of the system and an evaluation in patients for assessing the onset and duration of advanced PD motor symptoms.
A Mindful Way to Staying Mentally Healthy at UniversityBarry Tse
A deck prepared for an online talk given to the University of Liverpool students and staff in Feb 2022 Feel Good Month. The talk touched on common psychological issues identified in a recent study in the UK and explained some of the problems that plagued our modern lifestyle. Secular mindfulness is then introduced as a tool to regain control of our declining ability to focus and our stress response that has constantly been put on hyperdrive due to our evolution, neurological wiring, and psychological processes needed for our survival.
The document reports on a study that examined the relationship between general well-being and everyday memory. The study hypothesized that individuals with greater general well-being would have better everyday memory. 99 participants completed questionnaires measuring general well-being and everyday memory. A significant negative correlation was found, supporting the hypothesis that better general well-being is associated with better everyday memory. However, the study had limitations such as a small sample size and using self-report measures. Future research could explore this relationship further with a larger, more diverse sample.
Three hybrid classifiers for the detection of emotions in suicide notesJee-Hyub Kim
Suicides increasingly present a major concern in today's society. We describe our system for the recognition of emotions in suicide notes. Motivated by the sparse and imbalanced data as well as the complex annotation scheme, we have considered three hybrid approaches for distinguishing between the different categories. Each of the three approaches combines machine learning with manually derived rules, where the latter target very sparse emotion categories. The first approach considers the task as single label multi-class classification, where an SVM and a CRF classifier are trained to recognise fifteen different categories and their results are combined. Our second approach trains individual binary classifiers (SVM and CRF) for each of the fifteen sentence categories and returns the union of the classifiers as the final result. Finally, our third approach is a combination of binary and multi-class classifiers (SVM and CRF) trained on different subsets of the training data. We considered a number of different feature configurations. All three systems were tested on 300 unseen messages. Our second system had the best performance of the three,yielding an F1 score of 45.6% and a Precision of 60.1% whereas the best Recall (43.6%) was obtained using the third system.
Dr. Frederick Starr is a psychiatrist and pioneer in the field of neurotechnology. He founded Myneurva to advance neurofeedback treatment. Neurofeedback uses EEG to monitor brain activity and provide feedback to change brainwaves. It has been shown to effectively treat conditions like PTSD, ADHD, anxiety, depression, autism, and more. Dr. Starr's lecture discussed what neurofeedback is, how it works, the research supporting its use for various mental and physical health conditions, and the Starrbase system for remote neurofeedback treatment and diagnosis using QEEG brain mapping and artificial intelligence.
This document discusses key concepts in statistics including descriptive and inferential statistics, populations and samples, variables, and methods of collecting and presenting data. Specifically, it defines statistics, the two main types (descriptive and inferential), populations as all elements studied and samples as subsets of populations. It also outlines common variable types, methods of collecting data, different sampling techniques, how to construct frequency distributions and cumulative frequency distributions for qualitative and quantitative variables, and how to present data using bar charts and histograms.
O R I G I N A L P A P E RKnut W. Sørgaard Æ Peter Ryan Æ R.docxhopeaustin33688
O R I G I N A L P A P E R
Knut W. Sørgaard Æ Peter Ryan Æ Robert Hill Æ Ian Dawson and the OSCAR group
Sources of stress and burnout in acute psychiatric care:
inpatient vs. community staff
Received: 23 November 2006 / Accepted: 11 June 2007 / Published online: 13 August 2007
j Abstract Background Professionals who work
alone or in small teams often provide services for
people with serious mental health problems in com-
munity settings. Stress is common in community
teams and this may cause burnout and threaten the
quality and stability of the services. This study com-
pares levels of burnout and sources of stress among
community and acute ward staff in six European
centres. Methods A total of 6 acute ward (N = 204)
and community staff (N = 209) in 5 different Euro-
pean countries filled out the Maslach Burnout
Inventory (MBI), the Mental Health Professional
Scale (MHPSS) the Agervold Questionnaire for psy-
chosocial work environment (QPWES) in addition
to a comprehensive demographic questionnaire.
Results In the univariate analyses, except for Emo-
tional Exhaustion (MBI), there were no differences in
burnout between the two groups of staff. Community
teams reported more organisational problems, higher
work demands, less contact with colleagues, but also
better social relations and more control over their
work. The ward staff was more satisfied with the or-
ganisational structure and access to colleagues, but
complained about lack of control over operating
conditions at work. The multivariate analyses identi-
fied four groups of staff: (1) a Control-dissatisfied and
Contact satisfied group (N = 184) with 2/3 coming
from the wards. (2) A Contact-satisfied and Work-
demand dissatisfied group (N = 147) with 3=4 from
the community staff. (3) A Control- and Contact
dissatisfied group (N = 47) with a majority from
community teams, and (4) a Contact- and Work de-
mand satisfied group (N = 37) with a majority from
the wards. Conclusion Burnout as measured was not a
serious problem among community and ward staff
members, and did not differentiate between the two
groups. Acute ward working implied lack of control
but much contact with colleagues, whereas commu-
nity work entailed more control but demanding work
in terms of difficult task and hard-to-find-solutions.
j Key words stress – burnout – community care –
acute wards
Introduction
Professionals who often work alone or in small teams
are increasingly providing the care of people with
serious mental health problems in community set-
tings. Continuous structural changes in mental health
systems, with accompanying changes in role
requirements, exposes mental health professionals to
new sources of stress. Studies show that community
mental health staff experience considerable stress [6,
11, 20, 22] and that community work is more stressful
than working in a ward [5, 23]. Concerns have been
raised that such high levels of stress may cause de-
moralisation and burnout and thus threaten the
qual.
This document provides an overview of cognitive psychology and models of memory. It summarizes the multi-store model which includes sensory memory, short-term memory, and long-term memory. Evidence is presented for the capacity, encoding, and duration of short-term memory based on the research of Miller, Baddeley, and Peterson & Peterson. The working memory model is also summarized. Finally, applications to eyewitness testimony and memory improvement strategies are briefly discussed.
Visual Analytics for Healthcare - Panel at AMIA 2012 in ChicagoAdam Perer
AMIA 2012 Panel on Visual Analytics for Healthcare
Organizer:
Adam Perer, PhD
Research Scientist
IBM T.J. Watson Research Center, Hawthorne, NY
Panelists:
Ben Shneiderman, PhD
Professor, Computer Science
University of Maryland, College Park, MD
Yuval Shahar, PhD
Professor, Head of the Medical Informatics Research Center
Ben Gurion University, Beer Sheva, Israel
Jeffrey Heer, PhD
Assistant Professor, Computer Science
Stanford University, Stanford, CA
David Gotz, PhD
Research Scientist
IBM T.J. Watson Research Center, Hawthorne, NY
Abstract
With the proliferation of medical information technology, users at all levels of the healthcare system have access to more data than ever before6. This data can be of tremendous value but is often difficult to access and interpret. For example clinicians are often faced with the challenging task of analyzing large amounts of unstructured, multi-modal, and longitudinal data to effectively diagnose and monitor the progression of a patient’s disease4,5. Similarly, patients are confronted with the difficult task of understanding the trends and correlations within data related to their own health. At the institutional level, healthcare organizations are faced with the desire to use data to improve overall operational efficiency and performance, while continuing to maintain the quality of patient care and safety.
Recent advances in visualization and visual analytics have the potential to help each of the user groups listed above do more with the often overwhelming amount of data available to them 1,3,7,8. However, to be successful, visualization designers and clinicians must work together closely to ensure that the right technologies are used to help address the meaningful problems. Unfortunately, despite the continuous use of scientific visualization and visual analytics in medical applications, the lack of communication between engineers and physicians has meant that only basic visualization and analytics techniques are currently employed in clinical practice2,9.
The goal of this panel is to present state-of-the-art visualization applications for healthcare and engage the leading physicians and clinical researchers at AMIA to discuss the areas in healthcare where additional visualization techniques are most needed.
Similar to The Neural Correlates of Flow Experiences (20)
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumMJDuyan
(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏)-𝐏𝐫𝐞𝐥𝐢𝐦𝐬
𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
-Define entrepreneurship, distinguishing it from general business activities by emphasizing its focus on innovation, risk-taking, and value creation. Students will describe the characteristics and traits of successful entrepreneurs, including their roles and responsibilities, and discuss the broader economic and social impacts of entrepreneurial activities on both local and global scales.
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
Walmart Business+ and Spark Good for Nonprofits.pdfTechSoup
"Learn about all the ways Walmart supports nonprofit organizations.
You will hear from Liz Willett, the Head of Nonprofits, and hear about what Walmart is doing to help nonprofits, including Walmart Business and Spark Good. Walmart Business+ is a new offer for nonprofits that offers discounts and also streamlines nonprofits order and expense tracking, saving time and money.
The webinar may also give some examples on how nonprofits can best leverage Walmart Business+.
The event will cover the following::
Walmart Business + (https://business.walmart.com/plus) is a new shopping experience for nonprofits, schools, and local business customers that connects an exclusive online shopping experience to stores. Benefits include free delivery and shipping, a 'Spend Analytics” feature, special discounts, deals and tax-exempt shopping.
Special TechSoup offer for a free 180 days membership, and up to $150 in discounts on eligible orders.
Spark Good (walmart.com/sparkgood) is a charitable platform that enables nonprofits to receive donations directly from customers and associates.
Answers about how you can do more with Walmart!"
Gender and Mental Health - Counselling and Family Therapy Applications and In...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
Gender and Mental Health - Counselling and Family Therapy Applications and In...
The Neural Correlates of Flow Experiences
1. Neural Correlates of Flow Experiences
Richard Huskey
Michael Mangus
Christian Yoder
René Weber
http://medianeuroscience.org
Department of Communication
University of California Santa Barbara
2. •
•
•
•
•
•
Six Characteristics of Flow
Sense that one’s skills are an adequate fit for the challenge
Disappearance of self-consciousness
Loss of temporal awareness
Pleasant experience that not perceived as taxing
Perform the given activity “for its own sake”
Intense concentration; “there is no attention left” Csíkszentmihályi, 1990
Department of Communication
University of California Santa Barbara
3. Problem!
• Flow is often heuristically defined
• Flow measurement primarily relies on self-report measures
Method 1: Poorly Defined
Scales
Method 2: Experience
Sampling Method (ESM)
Department of Communication
University of California Santa Barbara
4. Synchronization Theory of Flow
• “Flow is a discrete, energetically optimized, and gratifying
experience resulting from the synchronization of
attentional and reward networks under condition of
balance between challenge and skill” (Weber, Tamborini, Westcott-Baker, &
Kantor, 2009, p. 412).
• Five assumptions central to sync theory:
– Neural networks can oscillate at the same frequency – networks oscillating at the same
frequency are said to be in sync
– Synchronization is a discrete state
– The synchronization of neural networks is energetically cheap
– The effect of networks in sync is greater than the sum of individual parts
– Flow results from a synchronization of attentional and reward networks under conditions
of a balance between challenge/skill
Department of Communication
University of California Santa Barbara
5. Synchronization Theory of Flow
• Early Support:
– fMRI Attention (Weber, Alicea, & Mathiak, 2009)
– fMRI Attention/Reward (Klasen et al., 2012)
– fMRI Neural Correlates of Flow (Ulrich, Keller, Hoenig, Waller,
Grön, 2013)
– STRT Attention (Kantor & Weber, 2009; Weber & Huskey, 2013)
– Patch Clamp Attention/Reward (Stanisor et al, 2013)
Department of Communication
University of California Santa Barbara
6. Weber & Huskey, 2013
Overall Model = .928, F(2,119) = 4.626, p = .012
All pairwise comparisons significantly different, p < .033
Overall Model = .68, F(2, 118) = 28.12, p < .001
All pairwise comparisons significantly different, p < .014
Department of Communication
University of California Santa Barbara
7. The Present Study
• This study adapted the Weber & Huskey (2013) protocol to a
brain imaging environment and predicts:
– Increased activation in alerting (frontal and parietal cortical
regions) and orienting networks (superior and inferior parietal
lobe regions, the frontal eye fields, and the superior colliculus)
during flow compared to boredom and frustration.
– Increased activation in reward networks (dopaminergic system,
the orbitofrontal cortex, the ventromedial and dorsolateral
regions of the prefrontal cortex, the thalamus, and the striatum)
during flow compared to boredom and frustration.
Department of Communication
University of California Santa Barbara
11. Analysis
•
Preprocessing:
– Design matrix with 120 s “on” + temporal derivatives +
confound Evs
– Gamma convolution
– McFLIRT + MELODIC ICA
– BET + 8 mm smooth + slice time correction + B0 unwarping
– Contrasts:
•
•
Boredom (-1), Flow (1)
Frustration (-1), Flow (1)
– Linear registration to structural scan + nonlinear registration
to MNII152 space
•
Main Analysis:
– 3 EVs (one for each contrast)
– Fixed Effects
– Cluster corrected at Z > 2.3, p < 0.05
Department of Communication
University of California Santa Barbara
12. Reward: Flow > Boredom
Left Thalamus2:
z = 3.01 (48,52,41)
1
Juelich Histological Atlas | 2 Harvard-Oxford Atlas | 3 MNI Structural Atlas
Department of Communication
University of California Santa Barbara
13. Attention: Flow > Boredom
Inferior Parietal
Lobe1: z = 4.17 (15,36,49)
1
Secondary Somatosensory
Cortex1: z = 3.31 (23,53,45)
Cerebellum3:
z = 3.73 (38,21,16)
Juelich Histological Atlas | 2 Harvard-Oxford Atlas | 3 MNI Structural Atlas
Department of Communication
University of California Santa Barbara
14. Results: Flow > Boredom
Frontal Pole1:
z = 3.36 (37,90,54)
1
Superior Temporal
Gyrus2: z = 3.59 (74,57,33)
Paracingulate
Gyrus2: z = 3.51 (41,86,32)
Juelich Histological Atlas | 2 Harvard-Oxford Atlas | 3 MNI Structural Atlas
Department of Communication
University of California Santa Barbara
15. Attention: Flow > Frustration
Visual Cortex (V1)1:
z = 3.26 (36,33,39)
1
Visual Cortex (V3)2:
z = 2.87 (53,19,33)
Visual Cortex (V4)2:
z = 3.04 (57,25,33)
Juelich Histological Atlas | 2 Harvard-Oxford Atlas | 3 MNI Structural Atlas
Department of Communication
University of California Santa Barbara
16. Attention: Flow > Frustration
Lateral Occipital
Cortex2: z = 3.14 (32,22,49)
1
Juelich Histological Atlas | 2 Harvard-Oxford Atlas | 3 MNI Structural Atlas
Department of Communication
University of California Santa Barbara
17. Concluding Thoughts
• Even with an n=1 study, we see promising results
– Flow > Boredom contrast results in activations most closely
related to sync theory predictions
– Flow > Frustration contrast is less clear – no clear reward
activation
• Limitations:
–
–
–
–
Does not test the synchronization component of Sync Theory
Differing modality between primary task and secondary task
Study design would benefit from increased automation
Non-random block order
Department of Communication
University of California Santa Barbara
We should begin by defining the characteristics of flow experiences.
Flow occurs when our skills are perfectly matched to the challenge we are taking on. Sometimes these challenges are as intense as driving a racecar. Other times they are as every-day as cooking dinner. The point is, flow occurs when there is a balance between challenge and skill
When we are in flow, we experience a loss of self consciousness. This is like the composer who described an almost out-of-body experience as he watched his hand write music.
We also lose track of time. I’m sure we’ve all been doing something enjoyable where we completely forget to monitor time, and are shocked at how much time has passed.
Flow is a pleasant experience that we don’t perceive of as taxing. Marathon runners, snowboarders, rock climbers hanging from precarious cliffs; these activities are both emotionally and physically taxing. But, in the moment, we don’t feel these effects. The climber doesn’t feel exhausted until reaching the summit.
Flow experiences are gratifying in and of themselves. The enjoyment comes from *doing* the activity, not completing the activity.
The last characteristic of flow is that is it is a wholly absorptive experience. In flow, we are so caught up in the experience that we do not have enough attention left to focus on anything else.
Flow measurement suffers two main issues:
Often heuristically defined
Primarily relies on self report measures
This leads to two problematic measurements of flow:
Questionnaires (everyone uses a different one)
The ESM… remember pagers?
So, why do you care? Several attempts have tried to resolve some of these issues by theorizing the neural correlates of Flow and using cognitive neuroscience to design unobtrusive and online measures of flow.
In the Communication discipline, flow has been theorized as the outcome of a synchronization between attentional and reward networks under conditions of a balance between challenge and skill.
Despite initial support, there still is insufficient evidence to either confirm or falsify the theory. This study attempts to falsify a central premise of Sync theory; that is, that attentional networks are a component of flow experiences.
Sync theory is based on an understanding of how complex neurobiological systems exchange information. While a full-scale test of Sync theory likely requires a brain imaging scanner, components of sync theory can be tested individually. This study isolates the assumption that attentional networks are central to flow experiences, and tests the role of attention in flow experiences.
Four assumptions of sync theory:
1). Neural networks can oscillate at the same frequency – networks oscillating at the same frequency are said to be in sync
Related to information exchange between complex neurobiological systems
2). Synchronization is instantaneous
Networks are synchronized or they are not. Just like you are in flow or not. Networks can’t be “more” or “less” in sync just as you can not be “more” or “less” in flow
3). The synchronization of neural networks is energetically cheap
Why flow experiences are not perceived as taxing
4). The effect of networks in sync is greater than the sum of individual parts
Why the experience of flow as qualitatively different from the individual components of each antecedent.
5). Result of a synchronization of attentional and reward networks under conditions of a balance between challenge/skill
Accounts for the wholly absorptive and highly rewarding nature of flow experiences.
In the Communication discipline, flow has been theorized as the outcome of a synchronization between attentional and reward networks under conditions of a balance between challenge and skill.
Despite initial support, there still is insufficient evidence to either confirm or falsify the theory. This study attempts to falsify a central premise of Sync theory; that is, that attentional networks are a component of flow experiences.
Sync theory is based on an understanding of how complex neurobiological systems exchange information. While a full-scale test of Sync theory likely requires a brain imaging scanner, components of sync theory can be tested individually. This study isolates the assumption that attentional networks are central to flow experiences, and tests the role of attention in flow experiences.
Four assumptions of sync theory:
1). Neural networks can oscillate at the same frequency – networks oscillating at the same frequency are said to be in sync
Related to information exchange between complex neurobiological systems
2). The synchronization of neural networks is energetically cheap
Why flow experiences are not perceived as taxing
3). The effect of networks in sync is greater than the sum of individual parts
Why the experience of flow as qualitatively different from the individual components of each antecedent.
4). Result of a synchronization of attentional and reward networks under conditions of a balance between challenge/skill
Accounts for the wholly absorptive and highly rewarding nature of flow experiences.
Weber & Huskey manipulated a video game and applied two measures of flow: a commonly used self-report measure (left chart) and a novel STRT measure of flow (right chart).
Results show that, consistent with a limited capacity model of attention, reaction times are longest under flow conditions (relative to boredom and frustration)
This result provides support for the attentional component of Sync Theory. What about the reward component?
We see support for:
(1) Attentional components of Sync Theory
(2) Reward Components of Sync Theory
There is a need to congruently assess attention and reward
Accordingly, this study predicts:
Experimental stimulus = star Reaction. We experimentally manipulate challenge. Explain all three experimental conditions, and give examples for why we did each.
Block design: Three conditions (boredom, frustration, flow). Two block per condition, a total of 6 blocks. Each block scans for 4 minutes.
48 trials per block. Each trial displayed for 1500 ms at irregular but non-random intervals per block. Interstimulus interval calculated by taking a sample of normally distributed randomly generated numbers (M = 1969 ms, SD = 1000 ms)
Experimental stimulus = star Reaction. We experimentally manipulate challenge. Explain all three experimental conditions, and give examples for why we did each.
Block design: Three conditions (boredom, frustration, flow). Two block per condition, a total of 6 blocks. Each block scans for 4 minutes.
48 trials per block. Each trial displayed for 1500 ms at irregular but non-random intervals per block. Interstimulus interval calculated by taking a sample of normally distributed randomly generated numbers (M = 1969 ms, SD = 1000 ms)
What we predicted:
Thalamus: component of reward network, switchboard for relaying sensory information (e.g., to attentional networks)
What we predicted:
Inferior parietal lobe: alerting network (endogenous and exogenous alerting)
Secondary Somatosensory Cortex: visceral sensation, touch, attention
Cerebellum: attention and motor control
What we didn’t expect:
Superior Temporal Gyrus: auditory & speech processing – likely due to different modality in attentional task
Paracingulate Gyrus (aPCC): predict future intention of social interactants? (Walter Adenzato, Ciaramidaro, Enrici, Pia, Bara, 2004, Journal of Cognitive Neuroscience)
Frontal pole: reasoning, planning, multitasking (Koechlin, 2011 – Trends in Cognitive Sciences), goal directed behavior?
What we Predicted:
Visual Cortex: processing of visual stimuli
What we Predicted:
Visual Cortex: processing of visual stimuli
Lateral Occipital Cortex: attention, object recognition Grill-Spector, Kourtzi, Kanwisher, 2001 – Vision Research)
In the Communication discipline, flow has been theorized as the outcome of a synchronization between attentional and reward networks under conditions of a balance between challenge and skill.
Despite initial support, there still is insufficient evidence to either confirm or falsify the theory. This study attempts to falsify a central premise of Sync theory; that is, that attentional networks are a component of flow experiences.
Sync theory is based on an understanding of how complex neurobiological systems exchange information. While a full-scale test of Sync theory likely requires a brain imaging scanner, components of sync theory can be tested individually. This study isolates the assumption that attentional networks are central to flow experiences, and tests the role of attention in flow experiences.
Four assumptions of sync theory:
1). Neural networks can oscillate at the same frequency – networks oscillating at the same frequency are said to be in sync
Related to information exchange between complex neurobiological systems
2). The synchronization of neural networks is energetically cheap
Why flow experiences are not perceived as taxing
3). The effect of networks in sync is greater than the sum of individual parts
Why the experience of flow as qualitatively different from the individual components of each antecedent.
4). Result of a synchronization of attentional and reward networks under conditions of a balance between challenge/skill
Accounts for the wholly absorptive and highly rewarding nature of flow experiences.