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Is The Brain an Analog Computer? Consciousness as Dynamic Brainwave Organization | Earl Miller

Professor Earl Miller discusses, Mind-Body Solution podcast.

Earl K. Miller is the Picower Professor of Neuroscience at the Massachusetts Institute of Technology. He has faculty positions in The Picower Institute for Learning and Memory and the Department of Brain and Cognitive Sciences. He holds degrees from Kent State University (B.A.) and Princeton University (M.A., Ph.D.) as well as an honorary Doctor of Science from Kent State University.

For decades, neuroscience treated the brain like a digital machine — storing information in synaptic connections and sustaining activity like a switch flipped on. But what if that model is incomplete?

In this conversation, I sit down with Earl Miller, MIT professor and head of the Miller Lab, to explore a growing shift in cognitive neuroscience: the brain may compute using dynamic electrical waves.

We discuss how oscillations coordinate millions of neurons, how waves interact with spikes in a two-way system, why large-scale brain organization may depend on rhythmic patterns, and what this means for artificial intelligence.

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The Man Who Stole Infinity

In 1874, German mathematician Georg Cantor published a groundbreaking paper showing that there are different sizes of infinity — a result that fundamentally changed mathematics by treating infinity as a concrete mathematical concept rather than a mere philosophical idea.

That paper became the foundation of set theory, a central pillar of modern mathematics.

Newly discovered letters from Cantor’s correspondence with fellow mathematician Richard Dedekind, believed lost until recently, suggest that a crucial part of the proof Cantor published came directly from Dedekind’s work.

Historian and journalist Demian Goos uncovered these letters while researching Cantor’s life. He found a key letter from November 30, 1873 that shows Dedekind’s proof of the countability of algebraic numbers — the same result Cantor would publish later under his own name.

Earlier histories had portrayed Cantor as a lone genius, but the new evidence reveals he relied heavily on Dedekind’s ideas and published them without proper credit, effectively erasing Dedekind’s role in the discovery.

Cantor’s strategy was partly tactical: because influential mathematician Leopold Kronecker vehemently opposed actual infinity, Cantor framed the paper under a less controversial title (about algebraic numbers), using Dedekind’s simplified methods to “sneak” in the revolutionary idea of comparing infinities.

The result was not just a new theorem but a new way of thinking about infinity, setting the stage for set theory and reshaping mathematics — even though the true story of its origins was more collaborative and ethically complicated than commonly told.

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Abstract: Emily Gutierrez-Morton

Yanchang Wang and colleagues (Florida State University) show that in yeast, polo-like kinase Cdc5 promotes the phosphorylation of SUMO protease Ulp2, reducing its affinity for SUMO chains and thereby facilitating polySUMOylation.

Genetics CellCycle

1Infectious Diseases Division, Department of Medicine and.

2Division of Plastic and Reconstructive Surgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA.

3Department of Mathematics, Dartmouth College, Hanover, New Hampshire, USA.

Abstract: Can we identify infections earlier in patients undergoing breast implant reconstruction?

Jeffrey P. Henderson use metabolomic profiling of postimplantation drain fluid, revealing an infection-associated molecular signature that, in longitudinal samples, substantially pre-dated clinical infection diagnosis.

1Infectious Diseases Division, Department of Medicine and.

2Division of Plastic and Reconstructive Surgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA.

3Department of Mathematics, Dartmouth College, Hanover, New Hampshire, USA.

Immune cells selectively pull DNA from dying nuclei, revealing a process dubbed nucleocytosis

Over the years, cell biology has built a detailed picture of how cells compartmentalize their internal functions. Central to this organization is the nucleus, which houses the genetic material and is separated from the cytoplasm by a robust nuclear envelope.

Traditionally, the nuclear membrane has been considered a strict barrier, maintaining nuclear integrity except during carefully controlled processes such as mitosis. As a result, the release of nuclear material has largely been associated with cellular damage or death.

However, recent work by a research team in Japan suggests that this view may be incomplete.

Spatiotemporal coordination of Slit-Robo repulsion and neurturin-Gfrα attraction guides multipolar migration during retinal lamination

Lehtimäki et al. reveal how repulsive Slit1b/2-Robo2 and attractive neurturin-Gfrα1/2-Ret signaling jointly coordinate multipolar migration of horizontal cells through crowded, scaffold-free environments of the vertebrate retina. This work was enabled by sophisticated transcriptomics analysis, targeted F0 CRISPR screening, and 3D fixed and live imaging.

Brain organoids can be trained to solve a goal-directed task

This research is the first rigorous academic demonstration of goal-directed learning in lab-grown brain organoids, and lays the foundation for adaptive organoid computation—exploring the capacity of lab-grown brain organoids to learn and solve tasks.

Using organoids derived from mouse stem cells and an electrophysiology system developed by industry partners Maxwell Biosciences, the researchers use electrical simulation to send and receive information to and from neurons. By using stronger or weaker signals, they communicate to the organoid the angle of the pole, which exists in a virtual environment, as it falls in one direction or the other. As this happens, the researchers observe as the organoid sends back signals of how to apply force to balance the pole, and they apply this force to the virtual pole.

For their pole-balancing experiments, the researchers observe as the organoid controls the pole until it drops, which is called an episode. Then, the pole is reset and a new episode begins. In essence, the organoid plays a video game in which the goal is to balance the pole upright for as long as possible.

The researchers observe the organoid’s progress in five-episode increments. If the organoid keeps the pole upright for longer on average in the past five episodes as compared to the past 20, it receives no training signal since it has been improving. If it does not improve the average time it keeps the pole upright, it receives a training signal.

Training feedback is not given to the organoid while it is balancing the pole—only at the end of an episode. An AI algorithm called reinforcement learning is used to select which neurons within the organoid get the training signal.

The results of this study prove that the reinforcement learning algorithm can guide the brain organoids toward improved performance at the cart-pole task—meaning organoids can learn to balance the pole for longer periods of time.

The researchers adopted a rigorous framework for success to make sure they were observing true improvement, and not just random success, including a threshold for the minimum time an organoid needs to balance the pole to “win” the game.

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Tumor-immune-neural circuit disrupts energy homeostasis in cancer cachexia

Tumor-immune-neural circuit in cancer cachexia.

The mechanisms involved in cancer-mediated cachexia and anorexia are not well understood.

The researchers in this study delineate an interplay among tumor cells, immune cells, and the nervous system that drives cancer cachexia and anorexia.

The authors show thay loss of GDF15 protects against appetite loss, muscle wasting, and fat loss in pancreatic, lung, and skin cancers.

Disrupting this feedforward loop with GDF15-neutralizing antibody, anti-CSF1R antibody, or Rearranged during Transfection (RET) inhibitor alleviates cachexia and anorexia across cancer models. sciencenewshighlights ScienceMission https://sciencemission.com/Tumor-immune-neural-circuit

Shi et al. delineate an interplay among tumor cells, immune cells, and the nervous system that drives cancer cachexia and anorexia. Specifically, tumor-derived CSF1 induces macrophage GDF15, which signals through the GFRAL-RET neural axis to enhance β-adrenergic activity and systemic wasting. Disrupting this feedforward loop alleviates cachexia across cancer models.

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Neurons receive precisely tailored teaching signals as we learn

How does the brain know which neurons to adjust during learning in order to optimize behavior? MIT researchers discovered that brains can use cell-by-cell error signals to do this — surprisingly similar to how AI systems are trained via backpropagation.

When we learn a new skill, the brain has to decide—cell by cell—what to change. New research from MIT suggests it can do that with surprising precision, sending targeted feedback to individual neurons so each one can adjust its activity in the right direction.

The finding echoes a key idea from modern artificial intelligence. Many AI systems learn by comparing their output to a target, computing an “error” signal, and using it to fine-tune connections within the network. A longstanding question has been whether the brain also uses that kind of individualized feedback. In a study published in the February 25 issue of the journal Nature, MIT researchers report evidence that it does.

A research team led by Mark Harnett, a McGovern Institute investigator and associate professor in the Department of Brain and Cognitive Sciences at MIT, discovered these instructive signals in mice by training animals to control the activity of specific neurons using a brain-computer interface (BCI). Their approach, the researchers say, can be used to further study the relationships between artificial neural networks and real brains, in ways that are expected to both improve understanding of biological learning and enable better brain-inspired artificial intelligence.

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