585 research outputs found

    Neuronal Glutamate Transporter EAAC1 Regulates Motor Activity and Anxiety in Mice

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    Obsessive Compulsive disorder (OCD) is a neuropsychiatric disorder characterized by the onset of recurrent thoughts, anxiety, and repetitive motor behaviors. The molecular basis of OCD remains elusive, but recent meta-analysis and genome-wide association studies (GWAS) suggest the existence of a genetic association between polymorphisms in the gene coding for excitatory amino acid carrier 1 (EAAC1) and OCD. It is also known that the Cortico-Striatal-Thalamo-Cortical (CSTC) pathway shows patterned hyperactivity in patients with OCD. EAAC1 is the primary neuronal glutamate transporter in the brain and is abundantly expressed in the cortex and the striatum, two regions that are part of the CTSC pathway. It is currently unknown whether mice that do not express the transporter EAAC1 have a behavioral phenotype consistent with that of OCD in humans, which would make them useful to study the molecular basis of the disease. Through a variety of behavioral tests our research examines phenotypic differences between wild-type C57BL/6 mice and conventional EAAC1 knockout mice (EAAC1-/-) to determine how EAAC1 regulates motor activity, anxiety, and coordinated information processing in the CSTC pathway. Our results suggest that the loss of EAAC1 expression is associated with the onset of motor hyperactivity and anxiety in mice of either sex. These behaviors are reminiscent of the repetitive behaviors and increased anxiety of patients with OCD. Taken together, these findings suggest that EAAC1-/- mice may be a valuable model in which to determine the molecular mechanisms underlying hyperactivity in the CSTC pathway and OCD

    Behavior Monitoring Using Visual Data and Immersive Environments

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    University of Minnesota Ph.D. dissertation.August 2017. Major: Computer Science. Advisor: Nikolaos Papanikolopoulos. 1 computer file (PDF); viii, 99 pages.Mental health disorders are the leading cause of disability in the United States and Canada, accounting for 25 percent of all years of life lost to disability and premature mortality (Disability Adjusted Life Years or DALYs). Furthermore, in the United States alone, spending for mental disorder related care amounted to approximately $201 billion in 2013. Given these costs, significant effort has been spent on researching ways to mitigate the detrimental effects of mental illness. Commonly, observational studies are employed in research on mental disorders. However, observers must watch activities, either live or recorded, and then code the behavior. This process is often long and requires significant eïŹ€ort. Automating these kinds of labor intensive processes can allow these studies to be performed more eïŹ€ectively. This thesis presents efforts to use computer vision and modern interactive technologies to aid in the study of mental disorders. Motor stereotypies are a class of behavior known to co-occur in some patients diagnosed with autism spectrum disorders. Results are presented for activity classification in these behaviors. Behaviors in the context of environment, setup and task were also explored in relation to obsessive compulsive disorder (OCD). Cleaning compulsions are a known symptom of some persons with OCD. Techniques were created to automate coding of handwashing behavior as part of an OCD study to understand the difference between subjects of different diagnosis. Instrumenting the experiment and coding the videos was a limiting factor in this study. Varied and repeatable environments can be enabled through the use of virtual reality. An end-to-end platform was created to investigate this approach. This system allows the creation of immersive environments that are capable of eliciting symptoms. By controlling the stimulus presented and observing the reaction in a simulated system, new ways of assessment are developed. Evaluation was performed to measure the ability to monitor subject behavior and a protocol was established for the system's future use

    Outsourcing labour to the cloud

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    Various forms of open sourcing to the online population are establishing themselves as cheap, effective methods of getting work done. These have revolutionised the traditional methods for innovation and have contributed to the enrichment of the concept of 'open innovation'. To date, the literature concerning this emerging topic has been spread across a diverse number of media, disciplines and academic journals. This paper attempts for the first time to survey the emerging phenomenon of open outsourcing of work to the internet using 'cloud computing'. The paper describes the volunteer origins and recent commercialisation of this business service. It then surveys the current platforms, applications and academic literature. Based on this, a generic classification for crowdsourcing tasks and a number of performance metrics are proposed. After discussing strengths and limitations, the paper concludes with an agenda for academic research in this new area

    A system for the visual detection and analysis of obsessive compulsive disorder

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    Computer vision is a burgeoning field that lends itself to a diverse range of challenging problems. Recent advances in computing power and algorithmic sophistication have prompted a renaissance in the literature of this field, as previously computationally expensive applications have come to the fore. As a result, researchers have begun applying computer vision techniques especially prominently to the analysis of human actions, in an increasingly advanced manner. Chief among the potential applications of such human action analyses are: human surveillance, crowd analysis, gait analysis and health informatics. Even more recently, researchers have begun to realise the potential of computer vision techniques, occasionally in conjunction with other computational approaches, to enhance the quality of life for people living with mental illness. Much of this research has focused on enhancing the existing, traditionally psychiatric, treatment plans for such individuals. Conventionally, these treatment plans have involved a mental health professional taking a face-to-face approach and relying significantly on subjective feedback from the individual, regarding their current condition and progress. However, recent computational methods have focused on augmenting such approaches with objective, e.g. visual, monitoring and feedback on an individual's condition over time. Of these approaches, most have focused on depression, bipolar disorder, dementia, or some form of anxiety. However, none of the approaches described in the literature has been aimed directly at addressing the issues inherent to patients with Obsessive Compulsive Disorder. Motivated by this, the proposed thesis comprises the design and implementation of a system that is capable of detecting and analysing the compulsive behaviours exhibited by individuals with Obsessive Compulsive Disorder. This is accomplished with the aim of assisting mental health professionals in their treatment of such patients. We achieved the aforementioned via a three-pronged approach, which is represented by the three core chapters of this thesis. Firstly, we created a system for the detection of general repetitive (compulsive) behaviours indicative of Obsessive Compulsive Disorder. This was achieved via the use of a combination of optical flow detection and thresholding, an image matching algorithm, and a set of repetition parameters. Via this approach, we achieved good results across a set of three tested videos. Secondly, we proposed a system capable of classifying behaviour as either compulsive or non-compulsive based on the differences in the repetition intensity patterns across a set of behavioural examples. We achieved this via a form of motion history image, which we call a 'Temporal Motion Heat Map' (TMHM). We produced one such heat map per behavioural example and then reduced its dimensionality using histogram-based pixel intensity frequencies, before feeding the result into a Neural Network. This approach achieved a high classification accuracy on the set of 40 tested behavioural examples, thus demonstrating its ability to accurately differentiate between compulsive and non-compulsive behaviours, as compared to a set of existing approaches. Finally, we built a system that is capable of categorising different types of behaviour, both compulsive and non-compulsive, and then assessing them for relative approximate anxiety levels over time. We achieve this using a combination of Speeded-Up Robust Features (SURF) descriptors for behaviour classification and statistical measures for determining the relative anxiety of a given compulsion. This system is also able to achieve a good accuracy when compared with other approaches

    Telehealth Acceptance and Commitment Therapy for Adolescents With Transdiagnostic Health-Related Anxiety: A Randomized Controlled Trial

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    Health-related anxiety is a growing issue to understand how to treat, particularly following the COVID-19 pandemic. Some studies show that a specific type of therapy, acceptance and commitment therapy (ACT), may be beneficial for health anxiety in adults, but this has not yet been tested with adolescents. The present study is a randomized, waitlist-controlled trial of ACT delivered via Zoom for adolescents struggling with health-related anxiety. A total of 30 adolescents (ages 12-17), plus one caretaker each (N = 60), living in Utah and currently struggling with health-related anxiety were enrolled. The majority of caretakers and adolescents were White, non- Hispanic/Latine, and female. Participants in the treatment condition received ten weekly, 50-minute sessions of ACT delivered via Zoom. Overall, adolescents who received ACT reported small, significant decreases in health-related anxiety as compared to the waitlist. No differences were found between groups for adolescent-rated general anxiety, depression, psychological inflexibility, or anxiety sensitivity. Caretakers reported decreases in child general anxiety and improvements in parental psychological inflexibility. No significant differences were found between groups for caretaker-rated familial accommodation and accommodation-related child distress. Overall, adolescents and caretakers rated the treatment positively. Future studies should test ACT with more diverse groups of adolescents as well as compare it to other available therapy options. However, this study is the first to examine ACT as a potential treatment for health-related anxiety in adolescents, and thereby adds to the growing literature supporting the use of ACT as a potential treatment option for youth

    Neuronal Glutamate Transporters Control Dopaminergic Signaling and Compulsive Behaviors

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    There is an ongoing debate on the contribution of the neuronal glutamate transporter EAAC1 to the onset of compulsive behaviors. Here, we used behavioral, electrophysiological, molecular, and viral approaches in male and female mice to identify the molecular and cellular mechanisms by which EAAC1 controls the execution of repeated motor behaviors. Our findings show that, in the striatum, a brain region implicated with movement execution, EAAC1 limits group I metabotropic glutamate receptor (mGluRI) activation, facilitates D1 dopamine receptor (D1R) expression, and ensures long-term synaptic plasticity. Blocking mGluRI in slices from mice lacking EAAC1 restores D1R expression and synaptic plasticity. Conversely, activation of intracellular signaling pathways coupled to mGluRI in D1R-containing striatal neurons of mice expressing EAAC1 leads to reduced D1R protein level and increased stereotyped movement execution. These findings identify new molecular mechanisms by which EAAC1 can shape glutamatergic and dopaminergic signals and control repeated movement execution

    Investigating transmembrane-lipid interactions of EphA2 and pH responsive peptides

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    Single-pass membrane receptor signaling plays vital roles in human development and maintaining homeostasis. These membrane receptors can also have causative functions in several diseases including cancer. Much is known about the structure and signaling outcomes of these receptors but the mechanistic details of how they pass an extracellular signal across the membrane and into cytoplasm via the transmembrane (TM) domain is unclear. It is further unknown how or if interactions with membrane lipids facilitate and/or regulate these events. Here we use the TYPE7 peptide to target the TM region of a receptor tyrosine kinase, EphA2. EphA2 engages in both tumorigenic (ligand-independent) and anti-tumorigenic (ligand-dependent) signaling making it an attractive drug target. From TYPE7 we learned that the activity of EphA2 could be modulated by interactions with a TM peptide. Findings from TYPE7 (Chapter II), lead to hypotheses about the signaling states of EphA2 and interactions with anionic lipids. We next demonstrated (Chapter III) that there is a TM conformation-specific coupling of juxtamembrane residues of EphA2 with PIP2 [phosphatidylinositol 4,5-bisphosphate]. Our data suggests that PIP2 promotes dimerization of EphA2 in the ligand-independent state, potentially regulating tumorigenic signaling. These findings add to the knowledge of the molecular events of EphA2 signal transduction which is vital to designing effective therapeutics. Finally, we investigated the effects that TM peptides can have on their lipid environments. We developed (Chapter IV) a fluorescence recovery after photobleaching (FRAP) protocol and an automated data analysis pipeline using programs written in Python and Mathematica languages for the determination of lipid diffusion coefficients. We used the pH responsive peptide (pHLIP) as a model TM domain and FRAP in supported lipid bilayers to investigate the effect of pHLIP on the rate of lipid diffusion

    Behavioural addiction-A rising tide?

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    The term 'addiction' was traditionally used in relation to centrally active substances, such as cocaine, alcohol, or nicotine. Addiction is not a unitary construct but rather incorporates a number of features, such as repetitive engagement in behaviours that are rewarding (at least initially), loss of control (spiralling engagement over time), persistence despite untoward functional consequences, and physical dependence (evidenced by withdrawal symptoms when intake of the substance diminishes). It has been suggested that certain psychiatric disorders characterized by maladaptive, repetitive behaviours share parallels with substance addiction and therefore represent 'behavioural addictions'. This perspective has influenced the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), which now has a category 'Substance Related and Addictive Disorders', including gambling disorder. Could other disorders characterised by repetitive behaviours, besides gambling disorder, also be considered 'addictions'? Potential examples include kleptomania, compulsive sexual behaviour, 'Internet addiction', trichotillomania (hair pulling disorder), and skin-picking disorder. This paper seeks to define what is meant by 'behavioural addiction', and critically considers the evidence for and against this conceptualisation in respect of the above conditions, from perspectives of aetiology, phenomenology, co-morbidity, neurobiology, and treatment. Research in this area has important implications for future diagnostic classification systems, neurobiological models, and novel treatment directions.This research was supported by a Grant from the Academy of Medical Sciences (UK) to Dr Chamberlain. Dr Chamberlain consults for Cambridge Cognition. Dr Grant has received research Grants from the National Center for Responsible Gaming, and Forest and Roche Pharmaceuticals. Dr Grant receives yearly compensation from Springer Publishing for acting as Editor-in-Chief of the Journal of Gambling Studies and has received royalties from Oxford University Press, American Psychiatric Publishing, Inc., Norton Press, and McGraw Hill. Dr. Goudriaan was supported by an innovative scheme Grant of the Dutch Scientific Association (ZonMw VIDI Grant no. 016.136.354) and received support from the European Association for Alcohol Research, the National Center for Responsible Gaming and has consulted for TĂŒV Germany. The other authors report no potential conflicts of interest or funding declarationsThis is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.euroneuro.2015.08.01

    Desenvolvimento de uma aplicação para ajudar pessoas com transtornos de ansiedade

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    This report documents the conception of the project Development of an application to help anxiety disorders. In this dissertation it is documented the analysis, design, development and evaluation of a mobile application and recommendation system that have the objective of helping people with anxiety. In recent years, recommendation systems have grown in popularity and appreciation with users searching for ease and convenience when receiving predictions and recommendations based on their preferences and characteristics. With anxiety disorders affecting a considerable percentage of the population, tools for anxiety self-management can help people who aren’t being accompanied by a therapist. The mobile application will have a variety of exercises that will provide ways for users to relieve their anxiety and provide tools for learning how to self-manage anxiety. The mobile application will be connected to a recommendation system which will be able to suggest anxiety relieving exercises to users by taking into account exercise ratings and user characteristics. To evaluate the general functionality of developed components tests were developed, with positive results. Additionally, the recommendation techniques were also tested to analyze the prediction error of each one. Overall the results were also positive with considerably low errors.Este relatĂłrio documenta a concepção do projeto Desenvolvimento de uma aplicação para ajudar pessoas com transtornos de ansiedade. Nesta dissertação Ă© documentado a anĂĄlise, desenho, desenvolvimento e avaliação de uma aplicação mĂłvel e sistema de recomendação que tĂȘm como objetivo ajudar pessoas com ansiedade. Nos Ășltimos anos, os sistemas de recomendação cresceram em popularidade e apreciação com os utilizadores procurando facilidade e conveniĂȘncia ao receber previsĂ”es e recomendaçÔes com base nas suas preferĂȘncias e caracterĂ­sticas. Com os transtornos de ansiedade afetando uma percentagem considerĂĄvel da população, as ferramentas para gerir a ansiedade podem ajudar pessoas que nĂŁo estĂŁo a ser acompanhadas por um psicĂłlogo. A aplicação mĂłvel terĂĄ uma variedade de exercĂ­cios que fornecerĂŁo maneiras para os utilizadores aliviarem sua ansiedade e fornecerĂŁo ferramentas para aprender como geri-la. A aplicação mĂłvel estarĂĄ conectada a um sistema de recomendação que poderĂĄ sugerir exercĂ­cios para alĂ­viar a ansiedade aos utilizadores, tendo em consideração as classificaçÔes dos mesmos e as caracterĂ­sticas do utilizador. Para avaliar a funcionalidade geral dos componentes desenvolvidos foram desenvolvidos testes, sendo os resultados positivo. AlĂ©m disso, as tĂ©cnicas de recomendação tambĂ©m foram testadas para analisar o erro de previsĂŁo de cada uma. Em geral os resultados tambĂ©m foram positivos com erros consideravelmente baixos

    Development of a self-help digital intervention for young people with Tourette syndrome

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    Young people (YP) with Tourette Syndrome (TS) and Tic Disorders (TD) experience difficulties with psychological wellbeing and reduced quality of life (QoL). Nonetheless, accessing healthcare support for these YP is difficult due to barriers including a lack of healthcare professionals, low healthcare coverage and reduced help-seeking behaviour of YP. Current psychological interventions for people with tics do not show the cost-savings or effectiveness to substantiate large-scale implementation. Interventions delivered digitally, utilising a self-help approach may overcome these limitations and have been shown to be effective in YP with mental health difficulties. Furthermore, the development of a wellbeing intervention using person, evidence and theory-based approaches could promote adherence and engagement to such an intervention. The current research aims to develop a digital self-help intervention to support and promote psychological wellbeing in YP with TDs. A person-based approach (PBA) was applied throughout. The research included a systematic review to assess similar interventions that were available for YP with TDs and YP with reduced psychological wellbeing. Qualitative research methods were used to interview YP with TDs, professionals who work with YP with TDs, and focus groups with parents and YP with TDs to explore what would be needed from such an intervention. Thematic analysis was used to code data inductively and a hybrid thematic analytical approach was used to apply deductive analysis to the data. The findings from across the methods were integrated to develop guiding principles and a logic model to support the future development of the intervention. The systematic review identified 985 studies, leaving 11 to be included in the review. Across the qualitative methods, 16 professionals, 51 YP and 35 parents or caregivers were recruited for interviews or focus groups. A digital health intervention (DHI) that would be suitably applied to YP with tics was not identified in the literature, and it was concluded that such an intervention would be desired by YP and thought useful by professionals. Many features and functions of the intervention were highlighted across participant groups, and the most important features were prioritised. These were combined with theory to develop guiding principles and a logic model. The research outputs include the development of guiding principles and a logic model, informed using the PBA, behaviour change theory and evidence. These findings will support future developers in creating an engaging and effective intervention for YP with tics, to promote and support their wellbeing
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