Zoya Mooraj

Zoya Mooraj

PhD Candidate: Cognitive Neuroscience

Zoya Mooraj - Cognitive Neuroscience of Aging

Introduction

Hi, I’m Zoya.

I am a PhD candidate in cognitive neuroscience at the Max Planck Institute for Human Development in Berlin. My research focuses on how changes in brain structure and function jointly shape cognitive aging.

Some main themes and research lines are outlined below.

Research Interests

Establishing robust structure-function-behaviour relations in aging

I investigate whether changes in white matter structure mediate the relationship between local BOLD variability and global brain organization. To learn a little more about this work, feel free to check out some posters presented at (link: DACC), (link: PuG) or slides from talks at (link: EUCAS)or (link: CNS).

In a closely related line of research, I am particularly interested in understanding the neural basis of age-differences and aging-related changes in metacognition. To investigate this, I study the dynamics of metacognition as a decision making process, considering different temporal dependencies and strategies that might manifest and govern this process. To learn a little more about this, feel free to check out slides from a talk of my doctoral program at the Royal Society, or presented in (link: Dr. Ngo’s lab meeitng).

Longitudinal modelling methods

A true understanding of aging-related changes in brain-behaviour relations requires longitudinal data. However, the challenge doesnt end with simply having longitudinal data. Some of the things I have explored are:

  • whether attrition is coupled to levels or slopes, and how this might be linked to our outcome of interest (particularly fMRI activity)
  • modelling longitudinal changes in and the effects of practice on confidence judgements and metacognition
  • difference scores as an (uninformed) case of regressed change

fMRI Denoising of Motion Artefacts

Working with developmental populations requires confronting some additional methodological challenges, such as extensive characterization and correction of movement artefacts. A particular type of these movements artefacts, spin history effects, are particularly pernicious, and I enjoy spending time thinking about how to best account for them. I am also working on a little tool to help detect just the extent of influence these may have on a given dataset (you can read more about this here: SHED).