Clara Sava-Segal

@csavasegal.bsky.social

PhD Student in the FINN Lab at Dartmouth https://csavasegal.github.io/

🧠 New preprint! How does the brain build specialized, efficient representations as we grow up? We used manifold learning to track the "intrinsic dimensionality" (ID) of brain activity in ~800 participants (aged 3mo–53yrs), as they performed naturalistic tasks and rested/slept.

Bild
bioRxiv Neuroscience@biorxiv-neursci.bsky.social · 2w ago

Developmental tuning of functional manifold dimensionality across the human brain https://www.biorxiv.org/content/10.64898/2026.07.24.740635v1

New paper 🧵! There's a lot of interest in how brain regions represent information in fMRI. One popular approach uses searchlights that roam across the brain to decode conditions. We built a method to uncover the sub-networks within searchlight maps.

Excited to be at #ohbm2026 @ohbmofficial.bsky.social presenting our real-time fMRI paper just published in @natneuro.nature.com ! come learn more at my talk on Wed at 9am in the symposium on “Closed-loop fMRI Neurofeedback” in Room E

Erica Busch@elbusch.bsky.social · 2mo ago

Our new paper is out this week in Nature Neuroscience! www.nature.com/articles/s41... We built a BCI that works with the brain's natural geometry — and we found that people could learn to play a video game with their brains in <1 hr of training. This efficiency is groundbreaking & here's why:

🎉New positions!🎉 Postdoc and Research technician openings in our lab @yale for computational psychiatry research. Technician position a great stepping stone to grad school. More info: rutledgelab.org/positions Work w/big data from our smartphone apps and large clinical samples happinessquest.app

Postdoc and Research Technician Positions — Rutledge Lab

Now hiring a postdoc and a research technician with an interest in neuroeconomics or computational psychiatry.

rutledgelab.org

Can you make your life feel “longer” in retrospect? Add a dose of change and novelty in the present to later expand memories of your past. Excited to share our work on how dopamine-related processing bends memory to reflect the passage of distinct events. newsroom.ucla.edu/releases/can...

Can dopamine bend time to shape memory?

The brain may use dopamine to expand time between distinct events, enabling us to remember unique episodes.

newsroom.ucla.edu

🚨🚨JOB ALERT🚨🚨 I'm hiring a cogsci/philosophy/compneuro postdoc at @ucl.ac.uk @uclbrainscience.bsky.social @uclpals.bsky.social! www.jobs.ac.uk/job/DRH486/p... Come to London & work on frameworks for "testing" for consciousness using Bayesian belief updating & latent variable modeling. Pls share!

Postdoctoral Research Fellow at UCL

Discover Postdoctoral Research Fellow jobs and more in higher education on jobs.ac.uk. Apply for further details on the top job board.

jobs.ac.uk

I defended my PhD 10 years ago today. That was the least remarkable thing that happened that day. Sharing something I wrote about it last year. Since then "the horrors persist but so do we." And with dignity.

BildBildBild

New preprint from Lindsey Tepfer (@ltjaql.bsky.social) and me! We silenced portions of internal monologues in two films to manipulate participants' access to characters' thoughts. Using ISC and RSA, we found that this aligned later neural processing of the narrative & encoding of trait impressions.

Figure 1. Experimental stimuli and paradigm. 1A. Manipulation timeline. Each video features a total of 12 IM moments, half of which were silenced in version 1, and the other half silenced in version 2. This produces two versions of each video where only half of the IMs are audible to the participant. 1B. Voice removal. Background sounds were preserved in both versions, regardless of IM presence. 1C. fMRI paradigm. Participants were randomly assigned a version and watched both videos in a counter-balanced order. 1D. Afterwards, they made trait ratings on each video’s main character in random order before rating them on subsequent traits. Figure 2. Scanner and online participant trait rating results. A. Scanner participants arrive at similar conclusions about characters across versions by the end of each video. B. Trait ratings at the end of the videos are correlated between online and scanner participants. C. The IM manipulation had a significant effect on the trait ratings across the duration of the videos, such that different versions led to different trait impressions. D. Participants who saw different versions changed their ratings for both clip types but changed to a greater degree after seeing the IM segments relative to the NIM.  Figure 3. ISC results. Gaining access to the same mental state knowledge in earlier IM clips led to significantly (p < .05, corrected) more aligned neural activity in subsequent NIM clips across a wide swath of the temporal lobe, as well as the frontal pole and SPL. Figure 4. Representational similarity analysis results. 4A. RSA pipeline.  Clip-specific patterns of brain activity were correlated across movies within segment type (NIM or IM) to create a correlation distance matrix for each participant. Corresponding trait ratings were partitioned into components specific to each of the two versions of each film or shared across both versions. RDMs based on those traits were used to predict the neural RDMs. The resulting coefficients were sorted into matched (version), unmatched (version), and shared across version, and inference was performed via t-tests across participants. See methods section for further details of this analysis. 4B. Prior trait rating results. 1. While watching IM clips of the same version, the prior trait ratings predict activity in the bilateral A1, STS, STG, and right VLPFC. 2. Prior trait rating predicts activity in these regions again in the same-version NIM clips. 3. Across the two versions, while watching the NIM clips, the prior trait ratings predicted activity in the right occipitotemporal cortex. 4C. Trait updating results. 1. While watching NIM clips, the right STS & MTG predict version-matched trait updating. 2. In the unmatched NIM clips, STS & MTG again predict trait updating. 3. Across the two versions, the precuneus and LOC show pattern similarity for trait updating in participants.
PsyArXivBot@psyarxivbot.bsky.social · 6mo ago

Access to others' internal monologues aligns neural processing of narratives and trait impressions: https://osf.io/7v9md