New preprint!.Why are long-range connectomic interactions in the cortex dominant in shaping dynamics in some experiments but apparently negligible in others? .We (w/ Rishi M, @eli_j_muller) address this by studying a new hybrid model of cortical dynamics.

RT @PMinervini: "in 2025 we will have flying cars" 😂😂😂

RT @conscious_tlab: ㊗️ our paper was finally accepted by Nature Communications! Data & paper are already accessible from here: . DREAM: A….

RT @ito_sosuke: こちらの論文、出版されてます。.一年半かけて不本意な結果に終わってしまったのは少し残念ではありますが、依然としてこの論文の価値は高く、最適輸送と熱力学の最新の技術がふんだんに使われた反応拡散の論文と….

RT @martinmbauer: At no point does this paper claim that "the 'Cosmic Microwave Background Radiation' can be explained entirely by the ener….

Rishi has done phenomenal wonderful work here in turning a half-idea I had (while lecturing undergrads on computational physics) into something quite interesting. Feedback welcome!.Paper is here: Code is here:

cf. fascinating insights into this complexity @jmacshine

It's possible that the brain exploits this specificity using spatially targeted cortical drives to facilitate rapid, distributed processing of sensory inputs (e.g., via core thalamic cells); but otherwise more spatially diffuse drives (e.g., via matrix thalamic cells).

So the model provides a potential explanation for the differential role of rapid, non-local projections in shaping geometrically constrained dynamics across experimental settings that vary in properties of the input drive and timescales of measurement.

Long-range connections play a key role in shaping dynamics for nearby spatially targeted inputs, but are less important for spatially diffuse inputs like in spontaneous dynamics. This might help explain why we see stronger non-local dynamics in targeted stimulation experiments

We find that the role of long-range connections in shaping dynamics is heavily timescale dependent, concentrated on fast dynamics <~30 ms, while slow dynamics resemble the geometric model. This could help explain why they are less important for capturing slower rs-fMRI dynamics

So Rishi developed a model to analyze long-range projections as a perturbation to geometric dynamics and thereby better understand why they might play different roles in different settings. The model dynamics combine wave propagation with 'worm-hole' shortcuts 🕳️🐛

And yet in many experiments, most compellingly in fMRI, 'smearing out' the connectome into a homogeneous geometric average (common in neural field theories) yields traveling wave dynamics that provide a surprisingly strong approximation for data (cf.

They can be considered as specific perturbations from a highly explanatory geometric rule for connectivity, as characterized by Roberts et al. (2016).

Long-range connections facilitate rapid communication between distributed cortical networks, are costly, heritable, and we clearly see their functional role in shaping dynamics experimentally, like the rapid non-local 'wormhole' 🕳️🐛 in this whisker-stimulation experiment

RT @riken_en: Call for participants!.The 2025 RIKEN International HPC Online Summer School is looking for graduate students and early-caree….

RT @AnnieGBryant: #OHBM2025 was a blast -- the perfect way to celebrate submitting my PhD thesis with y'all 🎉 . It was an honor to repres….

RT @ItaiYanai: hanging out with strangers in a campus pub should be considered part of the serious process of thinking .

RT @NSB_Lab: Good morning #OHBM2025! We still have several great posters to present today and tomorrow, so keep your eyes peeled 👀. 1573 -….

RT @SN_INGE: BREAKING NEWS.Congratulations to Professor Shun-ichi Amari!. 2025 Kyoto Prize Laureates.