CNNI PhD STUDENTS
Characterising and modulating paranoia in healthy high schizotypes and schizophrenia - a computational fMRI project.
Paranoia is the anticipation of threat and is a common mental experience in the healthy population as well as patients with schizophrenia. Despite such prevalence, paranoia, its causes and moderating factors are currently poorly understood and poorly managed, motivating the need for better understanding and treatment.
This PhD programme will continue and expand on a series of studies being conducted by the PI investigating neural, cognitive and psychological factors that lead to and maintain paranoid and delusional thinking. Using fMRI, bespoke social interaction tasks and cognitive test batteries, the selected student will lead a series of studies aiming to further delineate the processes involved in paranoid thinking and related symptomatology.
Drug/stress challenge paradigms, and computational modelling (with/without fMRI), conducted in with external collaborators at the Max Planck UCL Centre for Computational Psychiatry, are available tools to better understand how we model people’s intentions towards us dynamically over time and how we are able to, or fail to, assimilate new information into our beliefs which may lead to ‘delusional’ thinking styles.
A neuropsychological study of the role of cognitive load and working memory capacity in distraction suppression.
Selective attention allows us to ignore or actively suppress what is task-irrelevant and focus on what is task-relevant. According to the prominent 'load theory' of selective attention and cognitive control, the ability to focus attention improves under conditions of high perceptual load such as an increase in the amount of visual stimulation but deteriorates under conditions of high load on cognitive control processes such as working memory (Lavie & Dalton, 2013; de Fockert, 2013).
The primary objective of this project is to systematically investigate the neural correlates underpinning role of cognitive load on suppression of distracting visual stimuli in humans. We will also establish if measures of distractibility and working memory capacity can be used as diagnostic tests to predict which individuals in the general population are more susceptible to distraction in daily life under pressure such as while studying or working. The proposed work will confirm whether measures of distractibility could serve as potential markers to detect individuals with distractibility issues and promote early interventions.
Investigating neural mechanisms of episodic memory enhancement using transcranial direct current stimulation (tDCS) and magnetic resonance imaging (MRI).
Recent studies suggest that non-invasive brain stimulation techniques reduce the degree of forgetting, particularly if applied over dorsolateral prefrontal cortex. This effect has been reported both in young and old adults, suggesting these methods may have therapeutic potential, e.g. in people experiencing age-related memory problems.
My broader research interest is in shared neurophysiological mechanisms of cognitive and neurological conditions. I also contribute to teaching and marking on research methods and general psychology modules of the BSc Psychology course at the University.
An investigation of the effects of long-term cannabis use on brain function, chemistry and volume.
Cannabis is the most widely used illicit substance, my research is a multimodal project looking at the long term effects of cannabis on brain function, structure and chemistry. While a number of studies have used Magnetic Resonance Imaging to assess the effects of cannabis both acutely and non- acutely on brain function. Our research will be one of the first to combine Magnetic Resonance Imaging with GABA and Glutamate spectroscopy and comprehensive psychometric approaches to assess the difference in encoding and retrieval in cannabis users, differences in GABA and Glutamate distributions in frontal regions and on a more exploratory level; how the age of onset of use effects changes associated with the brain and performance of cannabis users on memory tasks.
Investigating evidence that late chronotypes (‘night owls’) are more at risk of developing depression than early chronotypes (‘early birds’)
My research is based on previous evidence that late chronotypes (‘night owls’) are more at risk of developing depression than early chronotypes (‘early birds’). I have been using behavioural techniques to identify if these at-risk individuals have differences in their emotional processing, reward-seeking or risk-taking behaviours. Additionally, I am using MRI techniques (including resting-state MRI, fMRI, MRS) to investigate whether late chronotypes have differences in the structure and/or function of their brain, which could explain why they are more prone to developing depression.
On a side note, I am also using functional spectroscopy (fMRS) to investigate and validate how well the BOLD signal is able to identify changes in neuronal activity in the amygdala – a region of the brain that has been shown to be affected by signal from local draining veins. This is important for my research since the amygdala is involved with processing emotional information and is therefore a key region of interest.
Evaluating if attentional control in people with high trait anxiety can be enhanced through closed-loop training (CLT) using rtfMR '
My PhD project will investigate the effect of real time fMRI-neurofeedback (rtfMRI-nf) training on attentional control in people with high trait anxiety. It will test the effects of rtfMRI-nf at neural and behavioural levels, and will also assess if trait anxiety levels are reduced by rtfMRI-nf training. On the neural level my study will focus on the frontal attentional network associated with the goal-directed attentional system (i.e. the DLPFC and dACC). Behaviourally, participants’ performance on attentional control tasks, with and without a threat component, will be examined. Participants’ trait anxiety levels will be assessed pre- and post-rtfMRI-nf training. The research will specifically test predictions derived from the Neurocognitive Framework for Attentional Control Theory (NFACT; Eysenck, Moser, Derakshan, & Allen, 2017). The study also aims to investigate the feasibility of using rtfMRI-nf to enhance attentional control in people with high trait anxiety and to provide crucial data and experience relating to the technical refinements for functional connectivity based rtfMRI-nf.