Recent volumetric brain reconstructions reveal high anatomic complexity. Research shows brain anatomy satisfies universal scaling laws, implying criticality in the cellular brain structure. Findings enable comparisons of structural properties across different organisms.
Researchers discovered that the brain interprets negated adjectives differently than affirmative ones, exhibiting a mitigating rather than inverting effect. This finding contributes to the understanding of how the brain processes negation and other complex linguistic operations.
The article discusses how machine learning is being used to calculate the macroscopic world that would emerge from string theory, a theory that posits the existence of tiny, invisible extra dimensions. These calculations have been difficult due to the enormous number of possibilities, but recent advances in artificial intelligence have made it possible to approximate the shapes of the Calabi-Yau manifolds, the objects that resemble loofahs and host quantum fields in string theory. The calculations have been able to reproduce the number of particles in the standard model, but not their specific masses or interactions. The long-term goal is to use these calculations to predict new physical phenomena beyond the standard model. The article also mentions that some physicists are skeptical of the usefulness of string theory and the role that machine learning will play in it.
A detailed map of the cells and synapses in a segment of a human brain sample has been created through a collaboration between Harvard and Google. The ultimate goal is to create a full map of a human brain like this, with each synapse and other structures detailed.
The study identifies two common forms of variation in human brain networks: border shifts and ectopic intrusions.
Border shifts involve changes in the borders between functional areas, while ectopic intrusions are shifts in brain organization at remote locations.
Both forms of variants are heritable but differ in their location, network associations, activations during tasks, and prediction of behavioral phenotypes.
New study on mice decision-making reveals that choice is not a singular moment but a reflection of the brain’s preexisting state.
The research, using Buridan’s Assay, suggests that the mice’s brain constantly broadcasts its goal, even before options are available, with patterns of neuron activity predicting choice.
Hunger and thirst don’t directly drive behavior; instead, they modulate the brain’s goal-setting, with an element of randomness causing switches between needs, ensuring both are met over tim