Treatment-resistant depression and chronic pain comorbidity: Cognitive-affective decline, neuroprotective factors and neurodegeneration risk (Alzheimer’s disease)
About this project
Project description
Aims (broad): To understand treatment-resistant depression, chronic pain comorbidity, and age-induced cognitive-affective decline: Exploring neuroprotective factors and neurodegeneration risk (Alzheimer’s)
Methodology (tentative)
Carrying out multi-site study, recruiting large, gender-balanced sample, and analyzing data from multiple assessments/measures (cognitive-affective assessment, neuroimaging, and biomarkers) might help us understand neuroprotective factors and assess neurodegeneration risk in aging population.
Phase 1 might be carried out in India, analyzing effect of cognitive-affective decline and chronic pain in traumatic brain injury to understand age-induced decline in presence of TBI (AIIMS, New Delhi).
Phase 2 might be carried out at UQ, analyzing large clinical dataset including cognitive-affective measure, pain measures, neuroimaging data, biomarkers (UQ)
Phase 3: Collating results from Phase 1 and Phase 2
Outcomes
It is expected that a multisite study with large dataset of multiple assessments of cognitive-affective measures, neuroimaging data, and biomarkers would offer insights to age-induced cognitive decline and neurodegeneration due to comorbidities (depression-chronic pain) and enable accurate prediction of clinical outcomes (cognitive impairment and onset of Alzheimer’s). Carrying out comparable/parallel studies in India and Australia helps us understand the role of environmental factors in cognitive decline and neurodegeneration.
Information for applicants
Essential capabilities
the prospective students should have some background in computer programming to be capable of grasping the neuroimaging analysis techniques.
Desireable capabilities
Research Design and Statistical Analysis, Cognitive/Neuropsychological Assessment
Expected qualifications (Course/Degrees etc.)
.): Master’s in Neuroscience, Neuroimaging, Neurophysiology, Computational Psychiatry, biomedical engineering