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computational model psychiatry

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https://www.readbyqxmd.com/read/27817095/polygenic-score-%C3%A3-intervention-moderation-an-application-of-discrete-time-survival-analysis-to-model-the-timing-of-first-marijuana-use-among-urban-youth
#1
Rashelle J Musci, Brian Fairman, Katherine E Masyn, George Uhl, Brion Maher, Danielle Y Sisto, Sheppard G Kellam, Nicholas S Ialongo
The present study examines the interaction between a polygenic score and an elementary school-based universal preventive intervention trial and its effects on a discrete-time survival analysis of time to first smoking marijuana. Research has suggested that initiation of substances is both genetically and environmentally driven (Rhee et al., Archives of general psychiatry 60:1256-1264, 2003; Verweij et al., Addiction 105:417-430, 2010). A previous work has found a significant interaction between the polygenic score and the same elementary school-based intervention with tobacco smoking (Musci et al...
November 5, 2016: Prevention Science: the Official Journal of the Society for Prevention Research
https://www.readbyqxmd.com/read/27798176/behavioral-and-neural-signatures-of-reduced-updating-of-alternative-options-in-alcohol-dependent-patients-during-flexible-decision-making
#2
Andrea M F Reiter, Lorenz Deserno, Thomas Kallert, Hans-Jochen Heinze, Andreas Heinz, Florian Schlagenhauf
: Addicted individuals continue substance use despite the knowledge of harmful consequences and often report having no choice but to consume. Computational psychiatry accounts have linked this clinical observation to difficulties in making flexible and goal-directed decisions in dynamic environments via consideration of potential alternative choices. To probe this in alcohol-dependent patients (n = 43) versus healthy volunteers (n = 35), human participants performed an anticorrelated decision-making task during functional neuroimaging...
October 26, 2016: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/27784534/toward-understanding-thalamocortical-dysfunction-in-schizophrenia-through-computational-models-of-neural-circuit-dynamics
#3
REVIEW
John D Murray, Alan Anticevic
The thalamus is implicated in the neuropathology of schizophrenia, and multiple modalities of noninvasive neuroimaging provide converging evidence for altered thalamocortical dynamics in the disorder, such as functional connectivity and oscillatory power. However, it remains a challenge to link these neuroimaging biomarkers to underlying neural circuit mechanisms. One potential path forward is a "Computational Psychiatry" approach that leverages computational models of neural circuits to make predictions for the dynamical impact dynamical impact on specific thalamic disruptions hypothesized to occur in the pathophysiology of schizophrenia...
October 23, 2016: Schizophrenia Research
https://www.readbyqxmd.com/read/27517087/computational-phenotyping-in-psychiatry-a-worked-example
#4
Philipp Schwartenbeck, Karl Friston
Computational psychiatry is a rapidly emerging field that uses model-based quantities to infer the behavioral and neuronal abnormalities that underlie psychopathology. If successful, this approach promises key insights into (pathological) brain function as well as a more mechanistic and quantitative approach to psychiatric nosology-structuring therapeutic interventions and predicting response and relapse. The basic procedure in computational psychiatry is to build a computational model that formalizes a behavioral or neuronal process...
July 2016: ENeuro
https://www.readbyqxmd.com/read/27150677/new-tools-for-new-research-in-psychiatry-a-scalable-and-customizable-platform-to-empower-data-driven-smartphone-research
#5
John Torous, Mathew V Kiang, Jeanette Lorme, Jukka-Pekka Onnela
BACKGROUND: A longstanding barrier to progress in psychiatry, both in clinical settings and research trials, has been the persistent difficulty of accurately and reliably quantifying disease phenotypes. Mobile phone technology combined with data science has the potential to offer medicine a wealth of additional information on disease phenotypes, but the large majority of existing smartphone apps are not intended for use as biomedical research platforms and, as such, do not generate research-quality data...
2016: JMIR Mental Health
https://www.readbyqxmd.com/read/27145766/dimensional-psychiatry-mental-disorders-as-dysfunctions-of-basic-learning-mechanisms
#6
REVIEW
Andreas Heinz, Florian Schlagenhauf, Anne Beck, Carolin Wackerhagen
It has been questioned that the more than 300 mental disorders currently listed in international disease classification systems all have a distinct neurobiological correlate. Here, we support the idea that basic dimensions of mental dysfunctions, such as alterations in reinforcement learning, can be identified, which interact with individual vulnerability and psychosocial stress factors and, thus, contribute to syndromes of distress across traditional nosological boundaries. We further suggest that computational modeling of learning behavior can help to identify specific alterations in reinforcement-based decision-making and their associated neurobiological correlates...
August 2016: Journal of Neural Transmission
https://www.readbyqxmd.com/read/27104961/precision-medicine-for-psychopharmacology-a-general-introduction
#7
Cheolmin Shin, Changsu Han, Chi-Un Pae, Ashwin A Patkar
INTRODUCTION: Precision medicine is an emerging medical model that can provide accurate diagnoses and tailored therapeutic strategies for patients based on data pertaining to genes, microbiomes, environment, family history and lifestyle. AREAS COVERED: Here, we provide basic information about precision medicine and newly introduced concepts, such as the precision medicine ecosystem and big data processing, and omics technologies including pharmacogenomics, pharamacometabolomics, pharmacoproteomics, pharmacoepigenomics, connectomics and exposomics...
July 2016: Expert Review of Neurotherapeutics
https://www.readbyqxmd.com/read/27038085/virtual-patient-simulation-in-psychiatric-care-a-pilot-study-of-digital-support-for-collaborate-learning
#8
Charlotta Sunnqvist, Karin Karlsson, Lisbeth Lindell, Uno Fors
Psychiatric and mental health nursing is built on a trusted nurse and patient relationship. Therefore communication and clinical reasoning are two important issues. Our experiences as teachers in psychiatric educational programmes are that the students feel anxiety and fear before they start their clinical practices in psychiatry. Therefore there is a need for bridging over the fear. Technology enhanced learning might support such activities so we used Virtual patients (VPs), an interactive computer simulations of real-life clinical scenarios...
March 2016: Nurse Education in Practice
https://www.readbyqxmd.com/read/27028297/a-complex-systems-approach-to-causal-discovery-in-psychiatry
#9
Glenn N Saxe, Alexander Statnikov, David Fenyo, Jiwen Ren, Zhiguo Li, Meera Prasad, Dennis Wall, Nora Bergman, Ernestine C Briggs, Constantin Aliferis
Conventional research methodologies and data analytic approaches in psychiatric research are unable to reliably infer causal relations without experimental designs, or to make inferences about the functional properties of the complex systems in which psychiatric disorders are embedded. This article describes a series of studies to validate a novel hybrid computational approach--the Complex Systems-Causal Network (CS-CN) method-designed to integrate causal discovery within a complex systems framework for psychiatric research...
2016: PloS One
https://www.readbyqxmd.com/read/27001617/system-based-proteomic-and-metabonomic-analysis-of-the-df-16-a-mouse-identifies-potential-mir-185-targets-and-molecular-pathway-alterations
#10
H Wesseling, B Xu, E J Want, E Holmes, P C Guest, M Karayiorgou, J A Gogos, S Bahn
Deletions on chromosome 22q11.2 are a strong genetic risk factor for development of schizophrenia and cognitive dysfunction. We employed shotgun liquid chromatography-mass spectrometry (LC-MS) proteomic and metabonomic profiling approaches on prefrontal cortex (PFC) and hippocampal (HPC) tissue from Df(16)A(+/-) mice, a model of the 22q11.2 deletion syndrome. Proteomic results were compared with previous transcriptomic profiling studies of the same brain regions. The aim was to investigate how the combined effect of the 22q11...
March 22, 2016: Molecular Psychiatry
https://www.readbyqxmd.com/read/26948484/trajectories-of-suicidal-ideation-in-patients-with-first-episode-psychosis-secondary-analysis-of-data-from-the-opus-trial
#11
Trine Madsen, Karen-Inge Karstoft, Rikke Gry Secher, Stephen F Austin, Merete Nordentoft
BACKGROUND: Heterogeneity in suicidal ideation over time in patients with first-episode psychosis is expected, but prototypical trajectories of this have not yet been established. We aimed to identify trajectories of suicidal ideation over a 3-year period and to examine how these trajectories relate to subsequent suicidality. METHODS: We used longitudinal data from the prospective 10-year follow-up OPUS trial of young Danish patients with first-episode psychosis...
May 2016: Lancet Psychiatry
https://www.readbyqxmd.com/read/26934301/modeling-transcranial-magnetic-stimulation-from-the-induced-electric-fields-to-the-membrane-potentials-along-tractography-based-white-matter-fiber-tracts
#12
Nele De Geeter, Luc Dupré, Guillaume Crevecoeur
OBJECTIVE: Transcranial magnetic stimulation (TMS) is a promising non-invasive tool for modulating the brain activity. Despite the widespread therapeutic and diagnostic use of TMS in neurology and psychiatry, its observed response remains hard to predict, limiting its further development and applications. Although the stimulation intensity is always maximum at the cortical surface near the coil, experiments reveal that TMS can affect deeper brain regions as well. APPROACH: The explanation of this spread might be found in the white matter fiber tracts, connecting cortical and subcortical structures...
April 2016: Journal of Neural Engineering
https://www.readbyqxmd.com/read/26906507/computational-psychiatry-as-a-bridge-from-neuroscience-to-clinical-applications
#13
REVIEW
Quentin J M Huys, Tiago V Maia, Michael J Frank
Translating advances in neuroscience into benefits for patients with mental illness presents enormous challenges because it involves both the most complex organ, the brain, and its interaction with a similarly complex environment. Dealing with such complexities demands powerful techniques. Computational psychiatry combines multiple levels and types of computation with multiple types of data in an effort to improve understanding, prediction and treatment of mental illness. Computational psychiatry, broadly defined, encompasses two complementary approaches: data driven and theory driven...
March 2016: Nature Neuroscience
https://www.readbyqxmd.com/read/26887012/quantitative-laughter-detection-measurement-and-classification-a-critical-survey
#14
Sarah Cosentino, Salvatore Sessa, Atsuo Takanishi
The study of human nonverbal social behaviors has taken a more quantitative and computational approach in recent years due to the development of smart interfaces and virtual agents or robots able to interact socially. One of the most interesting nonverbal social behaviors, producing a characteristic vocal signal, is laughing. Laughter is produced in several different situations: in response to external physical, cognitive, or emotional stimuli; to negotiate social interactions; and also, pathologically, as a consequence of neural damage...
2016: IEEE Reviews in Biomedical Engineering
https://www.readbyqxmd.com/read/26869840/emotor-control-computations-underlying-bodily-resource-allocation-emotions-and-confidence
#15
Adam Kepecs, Brett D Mensh
Emotional processes are central to behavior, yet their deeply subjective nature has been a challenge for neuroscientific study as well as for psychiatric diagnosis. Here we explore the relationships between subjective feelings and their underlying brain circuits from a computational perspective. We apply recent insights from systems neuroscience-approaching subjective behavior as the result of mental computations instantiated in the brain-to the study of emotions. We develop the hypothesis that emotions are the product of neural computations whose motor role is to reallocate bodily resources mostly gated by smooth muscles...
December 2015: Dialogues in Clinical Neuroscience
https://www.readbyqxmd.com/read/26779007/integrating-insults-using-fault-tree-analysis-to-guide-schizophrenia-research-across-levels-of-analysis
#16
Angus W MacDonald Iii, Jennifer L Zick, Matthew V Chafee, Theoden I Netoff
The grand challenges of schizophrenia research are linking the causes of the disorder to its symptoms and finding ways to overcome those symptoms. We argue that the field will be unable to address these challenges within psychiatry's standard neo-Kraepelinian (DSM) perspective. At the same time the current corrective, based in molecular genetics and cognitive neuroscience, is also likely to flounder due to its neglect for psychiatry's syndromal structure. We suggest adopting a new approach long used in reliability engineering, which also serves as a synthesis of these approaches...
2015: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/26415154/labeled-graph-kernel-for-behavior-analysis
#17
Ruiqi Zhao, Aleix M Martinez
Automatic behavior analysis from video is a major topic in many areas of research, including computer vision, multimedia, robotics, biology, cognitive science, social psychology, psychiatry, and linguistics. Two major problems are of interest when analyzing behavior. First, we wish to automatically categorize observed behaviors into a discrete set of classes (i.e., classification). For example, to determine word production from video sequences in sign language. Second, we wish to understand the relevance of each behavioral feature in achieving this classification (i...
August 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/26291157/translational-perspectives-for-computational-neuroimaging
#18
REVIEW
Klaas E Stephan, Sandra Iglesias, Jakob Heinzle, Andreea O Diaconescu
Functional neuroimaging has made fundamental contributions to our understanding of brain function. It remains challenging, however, to translate these advances into diagnostic tools for psychiatry. Promising new avenues for translation are provided by computational modeling of neuroimaging data. This article reviews contemporary frameworks for computational neuroimaging, with a focus on forward models linking unobservable brain states to measurements. These approaches-biophysical network models, generative models, and model-based fMRI analyses of neuromodulation-strive to move beyond statistical characterizations and toward mechanistic explanations of neuroimaging data...
August 19, 2015: Neuron
https://www.readbyqxmd.com/read/26160501/affective-cognition-exploring-lay-theories-of-emotion
#19
Desmond C Ong, Jamil Zaki, Noah D Goodman
Humans skillfully reason about others' emotions, a phenomenon we term affective cognition. Despite its importance, few formal, quantitative theories have described the mechanisms supporting this phenomenon. We propose that affective cognition involves applying domain-general reasoning processes to domain-specific content knowledge. Observers' knowledge about emotions is represented in rich and coherent lay theories, which comprise consistent relationships between situations, emotions, and behaviors. Observers utilize this knowledge in deciphering social agents' behavior and signals (e...
October 2015: Cognition
https://www.readbyqxmd.com/read/26157034/computational-psychiatry-towards-a-mathematically-informed-understanding-of-mental-illness
#20
REVIEW
Rick A Adams, Quentin J M Huys, Jonathan P Roiser
Computational Psychiatry aims to describe the relationship between the brain's neurobiology, its environment and mental symptoms in computational terms. In so doing, it may improve psychiatric classification and the diagnosis and treatment of mental illness. It can unite many levels of description in a mechanistic and rigorous fashion, while avoiding biological reductionism and artificial categorisation. We describe how computational models of cognition can infer the current state of the environment and weigh up future actions, and how these models provide new perspectives on two example disorders, depression and schizophrenia...
January 2016: Journal of Neurology, Neurosurgery, and Psychiatry
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