The Australian Dementia Network (ADNeT)
The Australian Dementia Networks (ADNeT) is an NHMRC funded research program which is bringing together Australia’s leading researchers, clinicians and consumers to create a powerful network for dementia prevention, treatment and care. Michael Breakspear is heading the ADNeT technology arm partnering with CSIRO, providing a harmonised platform and protocols across state and territory jurisdictions for the acquisition, storage and sharing of data for dementia research – a first for Australia. Renate Thienel is coordination the Newcastle ADNeT Screening and Trials arm, which seeks to reduce the duration of clinical trials in order to fast-track the development of effective therapies to prevent or treat dementia. Léonie Borne is working as a post-doctoral fellow on ADNeT, using machine learning to developing algorithms to identify suitable participants for clinical trials.
Prospective Imaging Study of Ageing (PISA): Genes, Brain & Behaviour
- Evidence of a robust link between cognitive decline and widening of cortical folds associated with progression to dementia.
- Prediction of AD using algorithms trained on healthy mid-life and older adults.
- Evidence that memory tests alone are insufficient to study the preclinical stage of AD and that other cognitive tests, such as those related to executive functions, are required to best identify individuals at risk.
Functional and structural brain networks in persons at high risk of bipolar disorder.
This ongoing collaboration with researchers at the University of NSW and University of Cambridge is now in the follow-up stage broadening into a longitudinal study of brain changes in a high-risk cohort. With the objective now being to better understand the progression of bipolar disorder (BD), given unaffected first-degree relatives of patients with BD have an odds ratio of ~7–14 of developing BD.
Following on from previously published work on the initial brain imaging dataset (Perry et al. (2019), Frankland et al. (2018), Roberts et al. (2018), Jenagathan et al. (2018)) and other broader research, structural and functional dysconnection amongst key brain networks supporting cognitive and affective processes have been highlighted in both persons with BD diagnosis and high-risk relatives. Work currently under review aimed to compare longitudinal structural connectivity changes in individuals at high genetic risk for BD to those without a family history of mental illness. Network-based statistics revealed that on-top of shared maturation changes in structural connectivity over time, high risk participants showed a subset of regions with weakened connectivity as compared to age-matched controls. This work to provides insight into and may present a candidate for predicting conversion to BD.
Control in an imprecise world: the cognitive control network, schizophrenia and active inference
Predictive processing in the negative symptoms of psychosis
Is emotion really as simple as smiling when you’re happy, and frowning when you’re angry? The mind combines multimodal information, including seeing, hearing and feeling the outside world, the inner sensation of organs such as the heart and gut, and our previous experiences, to construct the moment-to-moment emotions that we feel.
Impairments in facial expressivity, motivation, and sociality are the most debilitating features of psychotic disorders, yet they are inadequately treated. In this study, Jayson Jenagathan is using facial emotion detection algorithms, functional brain imaging, and novel tasks including real-time facial feedback and heart rate feedback, to discover the changes in the brain’s emotional circuits that underlie these symptoms.