The Biology Of Risk For Bipolar Disorder: Genetic Effects In A High-risk Longitudinal Study
Funder
National Health and Medical Research Council
Funding Amount
$856,412.00
Summary
Bipolar disorder is a severe mood disorder affecting over 350,000 Australians. Some children of bipolar disorder patients will also become ill, although currently we have no tools to predict which of these genetically at-risk young individuals will eventually develop symptoms. This study will use genetic information plus brain structural changes to predict which at-risk individuals are likely to become ill. This study will help elucidate early clinical and biological markers of bipolar disorder.
Using Reward-based Biomarkers To Improve The Early Detection Of Bipolar Disorder In Individuals Seeking Treatment For Depression
Funder
National Health and Medical Research Council
Funding Amount
$366,252.00
Summary
Bipolar disorder is often misdiagnosed as unipolar major depression, which can have disastrous clinical consequences. Emerging evidence indicates that individuals with bipolar disorder show particular dysfunctions within brain regions involved in processing reward. This research will use cutting-edge neuroscience methodologies to investigate reward processing in these two disorders, with the objective of identifying biological markers that help distinguish bipolar from unipolar depression.
Brain Connectivity Imaging Markers To Confirm Diagnosis For Bipolar Vs. Unipolar Depression – A Connectome Approach.
Funder
National Health and Medical Research Council
Funding Amount
$434,369.00
Summary
Differentiating Bipolar disorders from Unipolar Depression is a major clinical challenge. This misdiagnosis hinders optimal clinical care and has many deleterious consequences such self-harm, increased chances of suicide, poor prognosis, and greater health care costs related to this disorder. This project will provide urgently-needed advance in accurate identification of Bipolar disorders using Magnetic Resonance Imaging and remove one of the key obstacles to accurate diagnosis.
Automatic detection and modelling of acoustic markers of speech timing. This project aims to create new automatic sensing, analysis and assessment of cognitive, affective, mental and physical state from voice for mobile and computing devices. This project expects to generate new understanding of the effects of these states on detailed timing indicators of speech motor control, and new signal processing and machine learning methods that best exploit it. Expected outcomes from this project include ....Automatic detection and modelling of acoustic markers of speech timing. This project aims to create new automatic sensing, analysis and assessment of cognitive, affective, mental and physical state from voice for mobile and computing devices. This project expects to generate new understanding of the effects of these states on detailed timing indicators of speech motor control, and new signal processing and machine learning methods that best exploit it. Expected outcomes from this project include a new and accurate deep neural network framework for learning, analysing and detecting human states from speech automatically using articulatory timing markers. This should provide significant benefits, such as individually-tailored, frequent and low-cost automatic detection, monitoring and analytics for adverse states.Read moreRead less
Robots as a Social Group: Implications for Human-Robot Interaction. This Project aims to identify psychological factors that can limit the acceptance of robots in the home and workplace. As robots become more pervasive in everyday life, they are also likely to elicit fear, rejection, and even damage. The significance of the Project lies in its social neuroscientific approach to promoting better human-robot interaction by considering robots as a social group. Expect outcomes include theory develo ....Robots as a Social Group: Implications for Human-Robot Interaction. This Project aims to identify psychological factors that can limit the acceptance of robots in the home and workplace. As robots become more pervasive in everyday life, they are also likely to elicit fear, rejection, and even damage. The significance of the Project lies in its social neuroscientific approach to promoting better human-robot interaction by considering robots as a social group. Expect outcomes include theory development about human and robot intergroup acceptance, enhanced institutional and international collaborations, and much needed psychological knowledge for robot designers. Benefits include a detailed understanding of how to increase the acceptance of robots in a wide variety of fields.Read moreRead less
Social buffering of fear inhibition in adolescent rats. Adolescence is an important time when individuals learn to manage stress-related emotions like fear. Peers can help, or hinder, individuals to regulate fear. This project aims to understand how, when, and for whom social buffering of fear regulation occurs during adolescence. It uses a behavioural, pharmacological, and neural approach to explore these issues. The project aims to close the gap in understanding of how social companions affect ....Social buffering of fear inhibition in adolescent rats. Adolescence is an important time when individuals learn to manage stress-related emotions like fear. Peers can help, or hinder, individuals to regulate fear. This project aims to understand how, when, and for whom social buffering of fear regulation occurs during adolescence. It uses a behavioural, pharmacological, and neural approach to explore these issues. The project aims to close the gap in understanding of how social companions affect basic learning and memory processes in an understudied population of adolescents. The expected outcomes of this project include a richer knowledge of how peers shape emotional regulation during development, which will ultimately inform social-based approaches for improving emotion regulation in youth.
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