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spraveena/README.md

Praveena Satkunarajah

What I do

Hello there! My interest primarily lies understanding how our brain perceives and processes musical timbre, an important cue our brain relies on to segregate sound streams. My current work revolves around understanding how changes in plasticity or personal qualities (aging, musicianship) may affect neural representation of acoustic encoding along the auditory pathway and timescales, and the use of computational techniques to understand or model this process. I am also interested in the development of potential applications of auditory cognition in the use of rehabilitation.

My publications can be found here

I am currently a Postdoctoral Fellow at CAANLab in Memorial University of Newfoundland working on exploring how different musical timbres are encoded and represented in physiological signals under the supervision of Ben Zendel. I previously completed my BEng in Computer Science in Nanyang Technological University (NTU) in 2015 and completed my PhD in Neuroscience under the supervision of Dr Ben Zendel.

I am currently exploring postdoctoral opportunities in auditory and computational neuroscience, particularly projects involving evolving neural representation over timescales and the auditory hierarchy, auditory perception, EEG, and computational modelling. If my background aligns with your research—or with an opportunity in your network—I would be glad to connect!

I can be reached at:

Email
LinkedIn
Twitter

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  1. hmm_artifical_grammar_generator hmm_artifical_grammar_generator Public

    Used in: Tracking the emergence of a pitch hierarchy using an artificial grammar (2023). Frontiers in Cognition. by Satkunarajah, P., Sauvé, S.A., & Zendel, B.R.

    Python

  2. timbre_eeg_classification timbre_eeg_classification Public

    Models and Feature Extraction Functions Used in classification of single-trial EEG

    Python

  3. ffr_analysis ffr_analysis Public

    Computes Stimulus-to-Response Correlation (SRC) and FFT harmonics of already preprocessed and epoched Frequency Following Responses

    Python