Francisco Pereira

I'm recruiting PhD students to join my new lab in Fall 2026! The Shared Minds Lab at @usc.edu will combine deep learning and ecological human neuroscience to better understand how we communicate our thoughts from one brain to another.

Neural and behavioral reinstatement jointly reflect retrieval of narrative events - Nature Communications When people recall a movie, their eye movements and brain activity resemble those observed during the viewing. These behavioral and neural reactivations are linked through a common process, likely ref...

Excited to share our new paper w/ @cibaker.bsky.social in @natcomms.nature.com linking active vision & memory!

We provide evidence that gaze reinstatement & neural reactivation are deeply related phenomena that jointly reflect the experiences constructed during recall. doi.org/10.1038/s414...
🧵1/9

Because we must build good things while we scream about the bad, I have started a "Data for Good" team @data-for-good-team.bsky.social that partners with organizations needing short-term data science help. We have three projects ongoing & will add more as our capacity grows.
data-for-good-team.org

A network correspondence toolbox for quantitative evaluation of novel neuroimaging results - Nature Communications Here, the authors present the Network Correspondence Toolbox, which enables researchers to examine and report spatial correspondence between their neuroimaging results and widely used brain atlases.

It's finally here! Use the Network Correspondence Toolbox to help contextualize your neuroimaging findings 🧠

Test effects of behavior/events at every trial timepoint in photometry analyses! Paper with Erjia Cui, Dave Lovinger, Francisco Pereira. “A Statistical Framework for Analysis of Trial-Level Temporal Dynamics in Fiber Photometry Experiments.” Python+R packages! elifesciences.org/articles/95802. 1/13

People talk a lot about objects, but what about the softness of a cushion, the greenness of an emerald, or the viscosity of oil? In our work just published @pnas.org, we shed light on how we make sense of the hundreds of materials around us.
www.pnas.org/doi/10.1073/...

🚨We're very excited to share our latest study, by Pablo Diego and team:

"A polar coordinate system represents syntax in large language models",

📄: Paper arxiv.org/abs/2412.05571
🪧: Poster tomorrow: neurips.cc/virtual/2024...
🧵: Thread 👇

Gaze reinstatement & neural reactivation may be linked through a common process that reinstates past experiences during memory retrieval! doi.org/10.1101/2024...

Check out our #Preprint that integrates eye tracking into the Sherlock fMRI Dataset! Postdoc work w/ @cibaker.bsky.social 🧠🟦 #PsychSciSky

The Center for Multimodal Neuroimaging (CMN) and the FMRIF are hosting a workshop September 4-5 on “Insights Into Cognitive And Neural Function Through Eye Tracking”.

The hybrid workshop will be streamed on zoom, info: cmn.nimh.nih.gov/cmnworkshop2...

#eyetracking #neuroscience #cognition

Data Scientist This position serves as a Data Scientist and Senior Advisor to the NIDA Director and other leadership positions, on matters related to health informatics and data science, data management, and emergin...

The National Institute on Drug Abuse (NIDA) is seeking a Data Scientist and Senior Advisor to the NIDA Director and other leadership positions, on health informatics and data science, data management, emerging technologies, data standards and policy. More details at:
www.usajobs.gov/job/782086300

Thank you for the kind words, Sam! @gabeloewinger.bsky.social deserves most of the credit, both for spotting the need and then doing all the hard work to address it.

A logo of the National Institute of Mental Health

Interested in a researcher position studying the neural and computational bases of adaptive and maladaptive decision-making, and their relationship to mental health? Our colleague Silvia Lopez-Guzman is hiring a Data Scientist/Data Analyst, read more at cdn-lab.github.io .

We released a package implementing our framework. The methods can be applied to other neural data types too!

code: github.com/gloewing/pho...

Interested in learning more? Gabe Loewinger is giving a talk at SfN Monday 1pm in WCC-201
13/13

FLMM finds effects obscured by standard analyses! For example, FLMM reveals effects that "wash out" when analyzed with AUCs. In published work, Cue Period AUC finds no effects because it averages over time-windows (1) and (2) that have opposing effects. 12/13

FLMM can disentangle components with distinct temporal dynamics. It can also be used to run analogues of standard hypothesis tests (e.g., ANOVAs, correlations) at each trial time-point. Below is an example akin to the FLMM version of a paired t-test. 11/13

Informally, functional random-effects allow one to model variability across animals in the signal "shape." 10/13

Including functional random-effects allow one to model how the dynamics of signal-covariate associations vary across animals. 9/13

FLMM plots can be conceptualized as pooling signal values (dF/F) at a given trial time-point (e.g., 1.7 sec) across animals and trials, correlating it with covariate(s) (e.g., Latency-to-press) and plotting the slope of the correlation. 8/13

FLMM outputs a coefficient estimate plot that shows how the signal–covariate association evolves across trial time-points. 7/13

A plot showing the value of the model coefficient associated with a covariate, over the duration of a trial, time-locked to the lick event.

FLMM exploits autocorrelation to construct *joint* 95% CIs (light grey) that show time windows where effects are statistically significant (any intervals that do not contain 0). All you need to do is visually inspect! 6/13

A plot showing the value of the model coefficient associated with a covariate, over the duration of a trial, time-locked to the lick event.

FLMM combines the benefits of 1) Mixed Models to account for between-animal heterogeneity, and 2) Functional Regression to model covariate effects at each trial-time point. 5/13

A plot showing the value of the model coefficient associated with a covariate, over the duration of a trial, time-locked to the lick event.

Solution: We propose an analysis framework based on Functional Linear Mixed Models (FLMM) that allows one to analyze signal–covariate associations at every trial time point. 4/13

Problem: Photometry is often applied in nested longitudinal experiments with multiple trials per session and sessions per animal. This induces correlation, missing data, etc., that can obscure effects if not accounted for statistically. 3/13

Problem: Common photometry analysis methods reduce detection of effects because, among other things, they average across trials and use summary statistics (e.g., AUC, peak amplitude). 2/13

A plot showing fiber photometry time series for many trials.

If you use fiber photometry data and would like to test for the effects over time of stimuli, behavior, or any other variable, our new method may be of interest...

"A Statistical Framework for Analysis of Trial-Level Temporal Dynamics in Fiber Photometry Experiments"
www.biorxiv.org/content/10.1...