Itβs out!
22.02.2026 01:35 β π 208 π 27 π¬ 7 π 1Itβs out!
22.02.2026 01:35 β π 208 π 27 π¬ 7 π 1The bags kept piling up and eventually someone called the police, who rounded up the bags, even as more kept arriving. It made me realize that the code must have gotten stuck in a loop, and the humans were carrying out the functions in the real world, repeatedly, pointlessly. A real-world error log
05.02.2026 18:34 β π 4 π 0 π¬ 0 π 0One day last month, I watched as car after car after car stopped by my neighborβs house and dropped off a bag of vitamins each. It went on for hours, and almost as soon as one person had finished delivering and was walking away, another car arrived with another bag, etc etc
05.02.2026 18:31 β π 3 π 0 π¬ 1 π 0Why?
03.02.2026 12:54 β π 0 π 0 π¬ 1 π 03 funding rejections in a week π
28.01.2026 19:23 β π 6 π 0 π¬ 2 π 0
My review with @caterinagratton.bsky.social is (apparently) open access for those who couldn't see it before:
www.annualreviews.org/content/jour...
We discuss individual differences in brain network organization and how to home in on and talk about commonalities in the face of such differences
Happy to have you with us!
22.01.2026 14:56 β π 1 π 0 π¬ 0 π 0going through months of figure edits feels worth it when one ends up on a text book cover! thanks to @bradpostle.bsky.social and @rodbraga.bsky.social
15.01.2026 19:54 β π 12 π 2 π¬ 0 π 0
As a high-school student learning about science, I never even dreamed that my research would ever be on the cover of a textbook π₯Ή
Thank you @bradpostle.bsky.social !
And congrats to 1st author @donnisa.bsky.social !
www.amazon.com/Essentials-C...
** Recruiting a Postdoctoral Researcher! **
We are seeking a postdoc to help examine how brain networks might change within individuals across transitional times, such as adolescence & pregnancy!
Please share widely and apply at the link! #NeuroJobs
uva.wd1.myworkdayjobs.com/UVAJobs/job/...
Congrats Deniz! Looks fascinating!
09.12.2025 12:44 β π 2 π 0 π¬ 1 π 0β¦meaning, more crossover in general (conferences, projects, etc) between our fields
07.12.2025 13:23 β π 2 π 0 π¬ 0 π 0I agree there are parallels with questions weβve grappled with in neuroimaging for decades, now that wider field measurements are available in these models. Would be nice to have more crossover
07.12.2025 12:50 β π 2 π 0 π¬ 2 π 0Transparent and comprehensive statistical reporting is critical for ensuring the credibility, reproducibility, and interpretability of psychological research. This paper offers a structured set of guidelines for reporting statistical analyses in quantitative psychology, emphasizing clarity at both the planning and results stages. Drawing on established recommendations and emerging best practices, we outline key decisions related to hypothesis formulation, sample size justification, preregistration, outlier and missing data handling, statistical model specification, and the interpretation of inferential outcomes. We address considerations across frequentist and Bayesian frameworks and fixed as well as sequential research designs, including guidance on effect size reporting, equivalence testing, and the appropriate treatment of null results. To facilitate implementation of these recommendations, we provide the Transparent Statistical Reporting in Psychology (TSRP) Checklist that researchers can use to systematically evaluate and improve their statistical reporting practices (https://osf.io/t2zpq/). In addition, we provide a curated list of freely available tools, packages, and functions that researchers can use to implement transparent reporting practices in their own analyses to bridge the gap between theory and practice. To illustrate the practical application of these principles, we provide a side-by-side comparison of insufficient versus best-practice reporting using a hypothetical cognitive psychology study. By adopting transparent reporting standards, researchers can improve the robustness of individual studies and facilitate cumulative scientific progress through more reliable meta-analyses and research syntheses.
Our paper on improving statistical reporting in psychology is now online π
As a part of this paper, we also created the Transparent Statistical Reporting in Psychology checklist, which researchers can use to improve their statistical reporting practices
www.nature.com/articles/s44...
I worked with Jonny for 5 years during my formative years as a scientist. He influenced how I see life deeply. Although I won't hear him explain things to me again, his words and kindness will live through those whom he inspired. We were so lucky to have him in our lives. We miss you a lot, Jonny.
14.11.2025 23:54 β π 9 π 3 π¬ 1 π 0I was so lucky to have Jonny as my PhD supervisor. He was a one-of-a-kind scientist and person. He continues to be an inspiration to me and I will always be guided by the way he thought about science and life. He built an amazing network of wonderful people and we all miss you, Jonny.
14.11.2025 21:12 β π 19 π 5 π¬ 0 π 0Jonny Smallwood @themindwanders.bsky.social was a beloved friend and mentor. He was taken from us too soon. His was a beautiful mind who understood the beauty of minds. As ever before, his kind voice guides me and his work will continue. We miss you Jonny. www.cbs.mpg.de/news/obituar...
13.11.2025 15:19 β π 103 π 31 π¬ 15 π 8
Please see citations in the review
An exciting topic for future research!
/end
We also propose that these MTL connections may influence the emergence/separation of the 2 networks, DN-A and DN-B, during development/evolution:
Early spontaneous patterned activity within the MTL (e.g., traveling waves?) could 'tether' connected cortical regions into distinct networks:
We argue that these MTL connections help explain why these adjacent cortical networks have distinct functions:
π§ DN-A supports episodic thinking through its prominent connections to parahippocampal circuits
π§ DN-B supports theory of mind through its prominent connections to amygdala circuits
Recent work has demonstrated that these two networks are connected to distinct portions of the medial temporal lobe (MTL):
DN-A is connected to the parahippocampal cortex
DN-B is connected to the amygdala
Both networks appear to be in the anterior hippocampus, subiculum and entorhinal cortex
The two networks, DN-A and DN-B, support different forms of introspective thought.
DN-A is involved in recollection/prospection (e.g., thinking about the past or future)
DN-B is involved in theory of mind (e.g., thinking about someone else's thoughts).
Recently, individual-level "precision fMRI" has shown that the DN actually comprises multiple distinct networks (see image above)
The individualized network maps show much clearer separation between functions, suggesting that the overlap might have been a consequence of blurring in grouped data
Group-level estimates of the default network (DN) have long argued that it serves many introspective functions, including mentalizing (thinking about other people's thoughts, feelings & beliefs) and recollection/prospection.
Often noted was the heterogeneity but also overlap of functions in the DN:
How can the "default network" support many forms of introspective thought?
Our new review argues these functions rely on distinct MTL connections:
www.sciencedirect.com/science/arti...
Thanks to @denizvatansever.bsky.social & Jess Andrews-Hanna for the invitation to this Special Issue!
π§΅
Congratulations to you both! ππ½
30.10.2025 11:21 β π 2 π 0 π¬ 1 π 0Thank you @caterinagratton.bsky.social for inviting me to contribute to this! Fascinating to dive into the causes and consequences of individual differences in brain organization.
16.10.2025 15:59 β π 13 π 2 π¬ 0 π 0
Why do brain networks vary? Do these differences shape behavior? If every π§ is unique, how can we detect common features of brain organization?
@rodbraga.bsky.social and I dig in, in @annualreviews.bsky.social (ahead of print):
go.illinois.edu/Gratton2025-...
#neuroskyence #psychscisky #MedSky
π§΅π
Tagging co-authors:
@josephsalvo.bsky.social
Maya Lakshman
@aniaholubecki.bsky.social
@zeynepsaygin.bsky.social
Marsel Mesulam
...whatever the visual properties of those things.
Our work suggests that this specialization is shaped by connections to large-scale brain networks that aren't visual
So the interplay between visual and non-visual networks seems to shape the specialization of these late-stage visual areas