Earl K. Miller

Function is not tied to specific brain structures or time scales. The brain is not just a set of parts that each “do their own job”. Instead, networks are multifunctional and active across different speeds simultaneously. doi.org/10.1073/pnas.2… #neuroscience

The myth of the single-process brain: officially busted. 🧠New research shatters old assumptions by proving the human connectome runs multiple entirely separate, asynchronous information streams in parallel. It’s a multi-track orchestra using the exact same spatial blueprint. The ultimate game-changer? This proves high-speed EEG captures unique, high-fidelity connectome data completely independent of fMRI. This completely validates low-cost, standalone EEG as a powerful diagnostic tool—democratizing neurological care for patients who can’t access or undergo expensive MRI scans. #Neuroscience #BrainMapping #NeuroTech #MedTec h#HealthEquity #EEG #Connectome #MRI #EEG *Original Research: Open access. “Shared spatial and temporal principles govern connectome dynamics across timescales” by Anne-Lise Giraud, Jeremy Harper, Jonathan Wirsich, Maximillian Kirichenko Egan, Parham Mostame, Samar Wagih ElSayed, Sanmi Koyejo, Sepideh Sadaghiani, Sophia A. Giakas, Stephen M. Malone, Suhnyoung Jun, Thomas H. Alderson, William G. Iacono. PNAS DOI:10.1073/pnas.2535464123 - neurosciencenews.com/eeg-fmri-conne… via @neurosciencenew

This theory proposes that a deep cortical layer (layer 6b) may act like a coordinator, integrating top-down signals and neuromodulators. The layer 6b theory of attention cell.com/neuron/fulltex… #neuroscience

Reposted to fix typos. I hate typos.

How Your Brain Beats AI on the Energy of a Light Bulb - Earl K. Miller Neuroscience of Democracy Symposium May 19, 2026 MIT's Picower Institute for Learning and Memory youtu.be/uC8QlVgNIac @MIT_Picower @mitbrainandcog @ScienceMIT #neuroscience

Video: How Your Brain Beats AI on the Energy of a Light Bulb Earl K. Miller Neuroscience of Democracy Symposium May 19, 2026 MIT's Picower Institute for Learning and Memory youtu.be/uC8QlVgNIac @MIT_Picower @mitbrainandcog @ScienceMIT

Categories groups things into meaningful concepts. This review looks at how rodents do this. What they can and can’t learn, which brain circuits are involved, and how studying them could reveal the basic neural mechanisms. doi.org/10.1146/annure… #neuroscience

@CarlosEAlvare17 The burden of proof lies with those claiming AI is conscious. It is not “AI is conscious, prove me wrong.”

Like intelligence, we know other animals have consciousness and we have more of it. We know such traits are evolutionarily selected in an ecological context. We cannot keep moving the goalposts on AI performance or flipping the table with the argument we don't know what these things are/mean or how they work. My proposal is using pre-personal computer definitions and tests of intelligence, reasoning, abstraction, consciousness, etc. and comparing highly powered samples of randomly selected humans to AI. I was just predicting where the brain/AI trajectory is headed... x.com/CarlosEAlvare1…

This seems like a bold claim, given that we still don’t understand how consciousness works and current evidence suggests the brain operates differently from AI. A Silent Workspace In Claude Mirrors Key Features of Human Consciousness m.slashdot.org/story/456104 #neuroscience

@blsabatini @dimitrispp Indeed. Already cited in a forthcoming paper.

@MillerLabMIT @dimitrispp You might be interested in this experimental work showing that ephaptic coupling causing synchrony in the cerebellum pubmed.ncbi.nlm.nih.gov/30293822/

New paper! Electric fields generated by groups of neurons also feed back onto those neurons, creating a two-way interaction that may help organize activity patterns involved in memory. doi.org/10.1093/cercor… Work by @dimitrispp #neuroscience

Small-scale biological variation across regions plays a major role in organizing global rhythmic cortical dynamics. Spatially structured heterogeneity shapes large-scale cortical dynamics in a model of the human cortex doi.org/10.1073/pnas.2… #neuroscience

In learning, slower changes come from adjustments in connections between neurons, while faster changes come from intrinsic plasticity. Together, these two learning processes help the brain efficiently adapt to familiar information over time. nature.com/articles/s4146… #neuroscience

Cerebral Cortex Ephaptic coupling can explain variability in neural activity academic.oup.com/cercor/article…

Electric fields help guide neural activity, even from moment to moment. A new study adds evidence that electric fields in the brain help to organize and shape underlying neural activity via “ephaptic coupling.” picower.mit.edu/news/electric-… #neuroscience @mitbrainandcog @ScienceMIT

News alert: New paper! Electric fields help guide neural activity, even from moment to moment “The brain is a rollicking sea of electrical influences” picower.mit.edu/news/electric-… work by @dimitrispp #neuroscience

@VFD_org You might like this paper: Pinotsis, D.A. and Miller, E.K. (2026) Ephaptic coupling can explain variability in neural activity. Cerebral Cortex, in press. Preprint: doi.org/10.64898/2025.…

This is the deeper shift: flexible cognition may not be one fixed algorithm, but a manifold of lawful dynamical solutions. Different individuals can reach the same decision through different internal geometries, because context changes how evidence couples into a shared choice axis. Variability is not just noise around an average, it is part of the computational architecture itself.

The paper argues that two major puzzles (how the brain creates a unified experience and maintains an “edge-of-chaos” state) may be explained by continuous electromagnetic fields generated by neural activity. doi.org/10.3389/fncom.… #neuroscience

Computing in a memory with physics science.org/doi/10.1126/sc…

Analog computation is real, and your brain can take advantage of it. This chip does something similar, using natural electrical drift in its hardware to perform efficient analog computation. doi.org/10.1126/scienc… #neuroscience