Researchers from ISTA and Max Planck Institute have uncovered new details about molecular mechanisms driving memory processing at mossy fiber synapses in the hippocampus, crucial for memory formation.
The hippocampus is known to convert short-term memory into long-term memory. The study sheds light on how structural and functional changes in mossy fiber synapses may facilitate the encoding and storage of memories in the hippocampus.
The new research focuses on the mossy fiber synapse, a key connection point between neurons in the hippocampus. The scientists used a novel technique called "Flash and Freeze" combined with freeze fracture labeling to study the dynamic changes in proteins Cav2.1 calcium channels and Munc13 during signal processing. They found that upon stimulation, these proteins rearranged and moved closer together, enhancing neurotransmitter release and potentially contributing to memory formation.
The hippocampus is known to convert short-term memory into long-term memory. The study sheds light on how structural and functional changes in mossy fiber synapses may facilitate the encoding and storage of memories in the hippocampus.
The new research focuses on the mossy fiber synapse, a key connection point between neurons in the hippocampus. The scientists used a novel technique called "Flash and Freeze" combined with freeze fracture labeling to study the dynamic changes in proteins Cav2.1 calcium channels and Munc13 during signal processing. They found that upon stimulation, these proteins rearranged and moved closer together, enhancing neurotransmitter release and potentially contributing to memory formation.
A unique resource for hippocampus researchers and learners, offering tools to build and explore models of the hippocampus and its components using powerful modeling workflows.
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.
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.
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
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
consciousness relates to a dynamic process of self-sustained, coordinated brain-scale activity assisting the tuning to a constantly evolving environment, rather than in static descriptions of brain function (3–5). In that respect, neural signals combine, dissolve, reconfigure, and recombine over time, allowing perception, emotion, and cognition to happen (6).
