Planeamos revisar y discutir colectivamente los resultados de la encuesta en un Evento Satélite de la ASSC 2026. Únete a la organización del primer evento de la Sociedad Latinoamericana de la Conciencia!.

We plan to collectively review and discuss the results of the survey in a Satellite Event of the ASSC in Chile 2026 . Join us in the organization of the first event of the Latin American Consciousness Society!.

@medelero.bsky.social @cam-signorelli.bsky.social @em-fl.bsky.social

[🚨ALERTA LATAM🚨]
¿Quieres fortalecer la ciencia de la conciencia en América Latina? 🧠🌎

Completa esta breve encuesta (5–10 min) y únete a la creación de la primera Sociedad Latinoamericana para la Ciencia de la Conciencia.

Tu voz cuenta: forms.gle/iEd91YWVXcwH...

PS: @nature.com @natureportfolio.nature.com should really improve their editorial system to extract authors and affiliations from the submitted document. Adding 53 authors one-by-one, their emails and affiliations can be annoying. Do I really need to do this in the AI era?
Just saying...

Congrats and thanks to the whole team: 53 authors across 37 institutes across the world. Speciall thanks to William Wong, @naotsuchiya.bsky.social and @thomasandrillon.bsky.social !

We propose that a 'covert wake' mechanism may underly NREM dreams, where both wake and deep sleep brain dynamics coexist, enabling consciouss experience.

As a proof of concept, we demonstrated that dream experience can be detected from EEG signals both in REM and NREM sleep. Also, dream experience during NREM is associated with increased wake-like EEG activity embedded into slow wave activity.

The work provides an open and ever growing database with multicentric neural recordings of participants while sleeping and dreaming, in addition to sleep staging and phenomenological reports.

Database
👇
monash.edu/dream-database

Take-home: The next generation of brain mode discovery methods should explicitly optimize for synergy preservation. Leveraging synergy yields a more parsimounious and informative low-dimensional representation that retains a key qualitative property of large-scale brain dynamics: #synergy

9/9

Bonus track: Global signal regression enhances the discovery of synergistic interactions by reducing common sources of redundancy. See also www.nature.com/articles/s42...!

8/9

Main result: Autoencoders achieved the lowest reconstruction error while uniquely preserving synergistic interactions across all modes. PCA ranked second preserving neither synergy nor redundancy. The rest retained some synergy, but with higher reconstruction errors.

7/9

A systematic comparison: We derived low‑dimensional brain modes using PCA, diffusion maps, Laplacian eigenmodes, Yeo 7 resting‑state network (RSN) averaging, and a nonlinear autoencoder. Each method was constrained to 7 modes, aligning with the 7 @bttyeo.bsky.social RSNs.

6/9

We leverage #informationtheory to detect synergistic high-order interactions in resting‑state #fMRI. Synergistic interactions were consistently present across parcellations with different number of regions, prompting the question: do different DR methods also preserve synergy?

5/9

Dimensionality reduction methods aim to compress brain data mainly by minimizing redundancy. But what if we can go further by preserving and leveraging high-order synergistic interactions between brain modes? More information could be encoded within the same reduced space.

4/9

Dimensionality reduction of brain dynamics should be evaluated not only by reconstruction error or explained variance, but also by whether it preserves key qualitative properties of large-scale dynamics such as synergy.

3/9

Proposal: A complementary criterion for dimensionality reduction (DR) of brain dynamics (" #brainmodes ") based on preserving synergy. #Synergy is a recently characterized, still understudied property of the brain.

Synergy is information in the whole system that is not in the parts alone.

2/9