UCL Queen Square Institute of Neurology


Research Projects at UCL Queen Square Institute of Neurology

The research project is a vital element for those of you studying an MSc or MRes programme. The data driven projects below are a sample of those that can be completed physically on campus or remotely.

  • Analysis of neural data to probe the computations underlying learning, decision-making and/or knowledge representation 
  • Bioinformatics analysis of DNA methylation changes in FTDALS 
  • Characterizing the midkine-nidogen-2 interaction at the mouse neuromuscular junction. 
  • Cognitive assessments of patients with Parkinson’s disease using an online tool 
  • Data analysis of LFP of electrophysiology data from non-human primates conducting tasks involving learning and memory 
  • Data analysis of the neuronal computations underlying decision-making, working memory and learning 
  • Developing a multiplex in situ hybridisation and immunohistochemical (ISH-IHC) assay for detecting a spectrum of mitochondrial DNA (mtDNA) deletions and mtDNA depletion in relation to myofibre oxidative 
  • Does participation in an Intensive Comprehensive Aphasia Programme lead to clinically meaningful improvements in patient’s individualised short and medium term goals
  • Dynamical causal modelling of the prefrontal cortex during choice.
  • Establishing the relationship between the gut microbiome in industrial countries and the incidence of neurodegenerative diseases. 
  • Evaluation of Graphene-based electrophysiological probes to detect seizure onset zones. 
  • Exploring the relationship cortical atrophy measured with MR and gene expression in neurodegenerative diseases. 
  • Functional MRI of Epileptic Discharges Recorded Intracranially A New Modelling Approach. 
  • Genetic drivers of dementia in Parkinson’s disease.
  •  Hypothalamic volumetry in the FTD spectrum. 
  • In situ expression profiling of mitochondrial disease biomarkers FGF21 and GDF15 and OXPHOS defects in diagnostic muscle biopsies from children and adults with mitochondrial disease. 
  • Is there method in young peoples apparently random behaviour. 
  • Longitudinal analysis of progression of Parkinson’s disease in a large cohort study.
  • Modelling of learning and decision-making using reinforcement learning andor artificial neural networks. 
  • Norming and validation of a memory APP for use in temporal lobe epilepsy. 
  • Outcome of epilepsy patients rejected from epilepsy surgery program. 
  • Post-operative memory fMRI in Temporal Lobe Epilepsy. 
  • Quantitative fMRI Based on Intrinsic Connectivity Network Atlasing. 
  • Single cell sequencing of Alzheimer’s brain samples. 
  • Understanding molecular mechanisms that underlie the importance of new risk genes for Alzheimer’s disease and the ageing brain 
  • Validating a memory fMRI paradigm for Temporal Lobe Epilepsy . 
  • Visual dysfunction to predict cognitive change in Parkinson’s disease.