William Ngiam

William Ngiam

School of Psychology

Faculty of Health and Medical Sciences

Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.

I am a cognitive neuroscientist studying visual attention and working memory – in a nutshell, how we select relevant visual information and how is that information represented in mind and brain. I design psychophysical experiments that test the limits of visual perception and recall, hoping to link computational models of behaviour with patterns of neural activity to reveal the underlying neurocognitive mechanisms.

I am also an advocate for improving psychological science through open scholarship. I serve on the steering committee of ReproducibiliTea, a global journal club network that empowers early-career researchers to pursue reproducible research practices, and have made small contributions to initiatives such as the Framework for Open and Reproducible Research Training (FORRT) and the repliCATS project.

A banner for the Perception, Attention, Learning, and Memory (PALM) Lab



We can attend to only a few items at a time, so how and what we keep in mind is very important. In the current digital age, information is readily available at our fingertips, with algorithms designed to keep us glued to our devices and consume endless streams of content. This has lead to the collective feeling that our ability to focus our attention and our ability to discern information from misinformation is getting worse. My research hopes to improve understanding of our attention and cognitive systems, so that the world can regain focus on what is needed to meet the important challenges of today.

The Perception, Attention, Learning, and Memory (PALM) Lab studies our visual attention and working memory systems by linking patterns of brain activity to patterns of cognitive behaviour. We conduct experiments with psychophysics and neuroimaging (typically electroencephalography) methods, and use a combination of computational modeling and machine learning to decipher how humans select and keep information in mind for ongoing perception and cognition.

Research Projects

A GIF of the stimulus display in a working memory recall task known as conjunction whole-report

How are features bound together and stored in visual working memory?

The visual working memory system rapidly pieces together different visual features, such as color and shape, into perceived objects. At the same time, our visual working memory system can focus our attention on relevant items, filtering out irrelevant items and sometimes even irrelevant features! Our research aims to understand how various perceptual factors and cognitive factors influences working memory representations. In particular, how does featural information become bound into objects and stored in working memory, and whether this sets a sharp limit on how much we can hold in mind.

A GIF of the stimulus display in a multiple-object tracking and working memory task

How does experience and learning change how we attend to and store information in working memory?

There is a growing appreciation that our previous learning and experience can shape how we encode and represent information in mind. Our long-term memory system can readily shape how we attend to incoming visual information, at surprisingly early stages of visual processing. In particular, we are interested in how different types of learning (e.g. recognition training, statistical learning, associative learning) may improve the efficiency of the visual working memory system, whether this is achieved by changing working memory itself or circumventing its sharp capacity limit through other means.

A screenshot of the stimulus display in an orientation recall task

Decoding the contents of visual working memory using neuroimaging and multivariate classification

A recently developed decoder that applies machine learning classification to neuroimaging (EEG) data (called ‘mvLoad’) has located a multivariate neural signal that tracks working memory load (i.e. how many items are being stored in visual memory). This gives us an unprecedented window into the processes that underlie visual working memory in conjunction with how the brain actively maintains information. We measure electroencephalography (EEG) while subjects complete attention and working memory tasks that are designed to tap into theorized underlying processes. Then, we apply ‘mvLoad’ to see whether we can classify and map the changed contents of working memory.

  • Journals
    Year Citation
    2024 Ngiam, W. X. Q. (2024). Mapping visual working memory models to a theoretical framework. Psychonomic Bulletin and Review, 31(2), 442-459.
    DOI Scopus7 Europe PMC6
    2024 Brumback, A. C., Ngiam, W. X. Q., Lapato, D. M., Allison, D. B., Daniels, C. L., Dougherty, M., . . . Ye, H. (2024). Catalyzing communities of research rigour champions. Brain Communications, 6(3), 10 pages.
    DOI
    2024 Silverstein, P., Elman, C., Montoya, A., McGillivray, B., Pennington, C. R., Harrison, C. H., . . . Syed, M. (2024). A guide for social science journal editors on easing into open science. RESEARCH INTEGRITY AND PEER REVIEW, 9(1), 14 pages.
    DOI Europe PMC2
    2024 Jones, H. M., Diaz, G. K., Ngiam, W. X. Q., & Awh, E. (2024). Electroencephalogram Decoding Reveals Distinct Processes for Directing Spatial Attention and Encoding Into Working Memory. Psychological Science, 35(10), 1108-1138.
    DOI
    2024 Ngiam, W., Geng, J. J., & Shomstein, S. (2024). Editorial for Attention, Perception, & Psychophysics.. Attention, perception & psychophysics.
    DOI
    2023 Ngiam, W. X. Q., Loetscher, K. B., & Awh, E. (2023). Object-Based Encoding Constrains Storage in Visual Working Memory. Journal of Experimental Psychology: General, 153(1), 86-101.
    DOI Scopus1 Europe PMC1
    2023 Ngiam, W. X. Q., Foster, J. J., Adam, K. C. S., & Awh, E. (2023). Distinguishing guesses from fuzzy memories: Further evidence for item limits in visual working memory. Attention, Perception, and Psychophysics, 85(5), 1695-1709.
    DOI Scopus6 Europe PMC4
    2022 Parsons, S., Azevedo, F., Elsherif, M. M., Guay, S., Shahim, O. N., Govaart, G. H., . . . Terry, J. (2022). A community-sourced glossary of open scholarship terms. Nature Human Behaviour, 6(3), 312-318.
    DOI Scopus52 Europe PMC19
    2021 Ngiam, W. X. Q., Adam, K. C. S., Quirk, C., Vogel, E. K., & Awh, E. (2021). Estimating the statistical power to detect set-size effects in contralateral delay activity. Psychophysiology, 58(5), 10 pages.
    DOI Scopus12 Europe PMC5
    2019 Ngiam, W. X. Q., Brissenden, J. A., & Awh, E. (2019). "Memory compression" effects in visual working memory are contingent on explicit long-term memory. Journal of Experimental Psychology: General, 148(8), 1373-1385.
    DOI Scopus19 Europe PMC6
    2019 Ngiam, W. X. Q., Khaw, K. L. C., Holcombe, A. O., & Goodbourn, P. T. (2019). Visual Working Memory for Letters Varies With Familiarity but Not Complexity. Journal of Experimental Psychology: Learning Memory and Cognition, 45(10), 1761-1775.
    DOI Scopus33 Europe PMC14
    2018 Bateman, J. E., Ngiam, W. X. Q., & Birney, D. P. (2018). Relational encoding of objects in working memory: Changes detection performance is better for violations in group relations. PLoS ONE, 13(9), 12 pages.
    DOI Scopus4 Europe PMC1

  • Preprint
    Year Citation
    2023 Ngiam, W. X. Q., Loetscher, K., & Awh, E. (2023). Object-based encoding constrains storage in visual working memory.
    DOI
    2023 Ngiam, W. X. Q. (2023). Mapping visual working memory models to a theoretical framework.
    DOI
    2022 Ngiam, W. X. Q., Foster, J. J., Adam, K. C. S., & Awh, E. (2022). Distinguishing guesses from fuzzy memories: Further evidence for item limits in visual working memory.
    DOI
    2022 Goodbourn, P., Livesey, E. J., Ngiam, W. X. Q., Holcombe, A., & Forte, J. (2022). Learning and retention of new symbolic representations of number.
    DOI
    2022 Govaart, G. H., Schettino, A., Helbling, S., Mehler, D. M. A., Ngiam, W. X. Q., Moreau, D., . . . Paul, M. (2022). EEG ERP Preregistration Template.
    DOI
    2020 Ngiam, W. X. Q., Adam, K. C. S., Quirk, C., Vogel, E. K., & Awh, E. (2020). Estimating the statistical power to detect set size effects in contralateral delay activity.
    DOI
    2018 Ngiam, W. X. Q., Khaw, K. L. C., Holcombe, A. O., & Goodbourn, P. T. (2018). Visual working memory for letters varies with familiarity but not complexity.
    DOI

Course Coordinator

2024 (OTP5) – Applied Quantitative and Qualitative Methods

2024 (OTP6) – Understanding Synthesising Psychological Evidence

Lecturer

2024 (Semester 2) – Perception and Cognition (Concepts and Categories)

  • Editorial Boards
    Date Role Editorial Board Name Institution Country
    2024 - ongoing Editor Attention, Perception and Psychophysics Psychonomic Society United States
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