Research news on Biological neural networks

Biological neural networks as a research area focus on the structure, dynamics, and computation of networks of real neurons in living organisms, integrating cellular neurophysiology, synaptic plasticity, and systems-level circuit organization. The field investigates how biophysical properties, connectivity patterns, and neuromodulatory influences give rise to information processing, learning, memory, and behavior. It spans experimental and theoretical approaches, including electrophysiology, imaging, connectomics, computational modeling, and data-driven analysis of large-scale neural recordings, with the dual goals of explaining brain function mechanistically and providing biologically grounded principles that inform artificial neural network design and neuroengineering applications.

No brain required: This is how the single-celled Stentor learns

Scientists have known for more than a century that a single-celled organism with no nerve cells—much less a brain—can behave in ways that resemble learning. But those observations only went so far. How the organism did that ...

Fly ball: Drosophila can learn while playing with tiny spheres

For more than a century, the fruit fly has been a workhorse of the biological sciences that has helped scientists to make fundamental breakthroughs in fields such as genetics and neuroscience. As it turns out, human scientists ...

Building a reference manual for how cells connect with each other

Every multicellular organism, from tiny worms to humans, elephants, and whales, needs a way for their cells to connect with each other to form tissues, organs, and organize their overall body plan. Cells have a variety of ...

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