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I am a researcher in cognitive neuroscience motivated by a fundamental question: how does the brain give rise to individual differences in perception, memory, and social cognition? My work sits at the intersection of precision fMRI, computational modeling, and open-source research infrastructure.

Currently a Research Coordinator in the Poldrack Lab at Stanford University, I serve as the primary analyst for two of the largest dense-sampling fMRI datasets in the field — the Network study (N=46, 12 hrs/subject) and the RDoC study (N=65, 16.5 hrs/subject). I am applying to Ph.D. programs in Neuroscience with the goal of understanding how the brain infers others' mental states and encodes what we see and remember.

I am committed to open and reproducible science. All of my analysis code is publicly available, I use standardized data formats (BIDS) and validated preprocessing pipelines (fMRIPrep), and I contribute to open-source tools that make neuroimaging research more transparent and accessible to the community.

» Research Areas

Precision Functional Neuroimaging

Leading analysis of two precision fMRI studies — the Network study (N=46, 12 hrs/subject) and the RDoC study (N=65, 16.5 hrs/subject) — among the largest dense-sampling acquisitions in cognitive neuroscience. Exploring whether task-regressed residuals from diverse cognitive control tasks can substitute for resting-state scans in estimating individual-level functional networks.

dense-sampling fMRIprecision mappingindividual differencesresting-state

Cognitive Control & Neural Ontology

Applying exploratory factor analysis to fMRI contrast maps across multiple cognitive control paradigms to test whether NIMH RDoC constructs correspond to separable neural circuits. Initial results reveal both domain-general factors reflecting task-positive activation and contrast-specific factors — a step toward a data-driven ontology of cognitive control.

RDoCfactor analysiscognitive controlfMRI contrasts

Individual Differences & Computational Methods

Implementing MVPA and hierarchical Bayesian parcellation methods to characterize individual differences in functional architecture. Earlier work applied drift-diffusion models to quantify how face masks affect evidence accumulation for facial emotion processing.

MVPABayesian parcellationdrift-diffusionEEG/ERP

Research Software Engineering

Building open-source tools and infrastructure for reproducible neuroimaging research. Refactored the lab's end-to-end fMRI pipeline encompassing BIDS conversion, preprocessing orchestration (fMRIPrep, MRIQC, QSIPrep), and reproducible GLM specification. Built CI/CD infrastructure with DataLad for complete data provenance.

fMRIPrepDataLadCI/CDjsPsychBIDS

» Publications

PreprintSharing control with a machine impairs human response inhibition

Bissett, P., Achyutuni, K., Rios, J. H., Jones, H. M., Bennett, L., & Poldrack, R.

Preprint (2025)

Arbitrary stimuli are not devalued by stopping action: A registered replication of Wessel et al. (2014)

Bissett, P. G., Achyutuni, K. G., Li, J. K., Jones, H. M., Shim, S., Rios, J. A. H., Bennett, L. J., et al.

Journal of Experimental Psychology: General, 154(11), 2935--2943 (2025) · DOI

Within-Person Temporal Associations Among Self-Reported Physical Activity, Sleep, and Well-Being in College Students

McGowan, A. L., Boyd, Z. M., Kang, Y., Bennett, L., Mucha, P. J., Ochsner, K. N., Bassett, D. S., Falk, E. B., & Lydon-Staley, D. M.

Psychosomatic Medicine, 85(2), 141--153 (2023)

» Selected Presentations

Shared control impairs cognitive control: Human response inhibition slows when machines fail to inhibit

Bissett, P., Achyutuni, K. G., Rios, J. H., Jones, H. M., Bennett, L., & Poldrack, R.

The Cognitive Science Society, San Francisco, CA (2025)

Characterizing cognitive control networks using a precision neuroscience approach

Bissett, P. G., Shim, S., Bennett, L. J., Rios, J. A. H., Jones, H. M., Hagen, M. P., et al.

Organization for Human Brain Mapping (2025)

Mapping task measures to latent constructs: An expert survey of the NIMH RDoC cognitive domain

Bissett, P. G., Bennett, L., Rios, J. A. H., Shim, S., McKee, P. C., Iyer, C. S., Ram, N., Poldrack, R. A.

Organization for Human Brain Mapping (2024)

See all presentations on CV →

» Cognitive Task Demo

The stop-signal task is one of the most widely used paradigms for studying response inhibition. On each trial you see an arrow and must press the corresponding key as quickly as possible -- unless the arrow turns red, in which case you should withhold your response. Try it below.

Stop-Signal TaskReady

Press left/right arrow keys to match the arrow direction.

If the arrow turns red, do not press anything.

12 trials · ~30 seconds