LAIYBA RAZZAQ

MSc in Cognitive Neuroimaging and Data Science with clinical experience as Neurorehabilitation and Speech & Language Therapy Assistant. Expertise in translating complex neuroscientific data into actionable insights using neuroimaging methods and computational modelling. Proven ability to support patients with neurological conditions through targeted therapeutic interventions and collaboration with multidisciplinary teams. Committed to advancing healthcare and research through scientific expertise and innovative practices.

Understanding Perceptual Decision-Making in Autism Spectrum Disorder and Developmental Dyslexia Using Time-Varying Drift Diffusion Models – MSc Dissertation  

Applied hierarchical Bayesian modelling to a large neurodevelopmental dataset to compare the traditional DDM with the Time-Varying Drift Diffusion Model (TVDDM). Demonstrated that the TVDDM provided superior fits to children’s behavioural data, capturing dynamic evidence-accumulation processes. Identified developmental differences in growth-shape exponents, boundary separations, and non-decision time, showing that developmental stage—more than diagnostic category—drives variation in perceptual decision dynamics. Highlighted the value of dynamic computational modelling for understanding neurodivergent cognition.

Replication of Jessica Cohen’s fMRI Analysis Pipeline – MSc Project (University of Birmingham)

Methods: FSL (v6.0.5.1), MCFLIRT, BET, FEAT, GLM, preprocessing + first-level modelling
Replicated the full fMRI preprocessing and analysis pipeline from Cohen’s seminal Stop-Signal Task study, implementing robust anatomical and functional preprocessing (BET skull stripping, motion correction, slice-timing correction, spatial smoothing, linear EPI-to-T1 and T1-to-MNI registration). Constructed event-based GLMs to model inhibitory control processes and reproduced Cohen’s contrast of interest (“stop_correct > go_correct”). Demonstrated technical proficiency in command-line scripting, automated batch-processing, and rigorous parameter justification grounded in neuroimaging literature.

The Significance of Misrepresentation of One’s Faith: A Qualitative Study of Islamic Religious Identity in Western Culture – BSc Dissertation

Conducted a thematic analysis of semi-structured interviews exploring how Muslims experience and interpret misrepresentation of their faith within Western social and media contexts. Identified four core themes: media-driven stereotyping, visual appearance and modesty norms (e.g., hijab), lack of religious education, and historical/political narratives shaping public misconceptions. Delivered a theoretically grounded, culturally informed contribution to the discourse on identity, prejudice, and intergroup perception.

Computational Modelling Portfolio – MATLAB

Completed a suite of computational neuroscience and modelling labs using MATLAB, developing and analysing neural field models, control systems, Bayesian multisensory estimators, multi-state learning models, agent-based segregation simulations, synchronisation and feedback controllers, tactile afferent simulations, and Gaussian/DoG vision filters. These projects strengthened my ability to design, implement, and interpret complex computational models across perception, learning, and dynamical systems.