An innovative new model helps predict how damaging conditions in the brain can be triggered by complex dynamics in branching neural networks.
Fear and anxiety share overlapping neural circuits. The findings contradict the popular belief that anxiety and fear are distinct emotions with different triggers and segregated brain circuits.
A new computational model predicts how information deep inside the brain could flow from one network to another, and how neural network clusters can self optimize over time.
Microglia, immune cells that protect the brain from infection and inflammation, also appear to play a critical role in sculpting circuits in the developing brain.
Discovery reveals neurons can lose their individuality in some conditions. The findings contradict the conventional belief that neurons always stay separated and never fuse.
Researchers have identified a new role of bi-directional connections for accelerating communication between brain networks.
Cortical thickness and regional brain connectivity pay an equally important role in linking brain and behavior.
APOEe4, a gene associated with Alzheimer's disease risk, doesn't appear to directly affect memory performance or brain activity in older adults without cognitive impairment. However, the gene does seem to influence brain regions and systems that older at-risk adults activate to support successful memory recall.
The activity of a network of dopamine neurons reflects both the innate preferences for smell and taste, as well as the physiological state of fruit flies.
Examining the brains of frequent cannabis users, researchers have identified a pattern of connectivity related to craving the substance. The findings add weight to the idea that brain regions do not work in isolation, but via the connectivity of multiple networks that signal to each other depending on state and need. Brain connectivity during cannabis cravings is not static but has fluctuations in connection patterns between the central executive network and nucleus accumbens.
A new system for high-density EEG helps with the imaging of the origin and path of both normal and abnormal neural activity.
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··4 min readA new machine-learning algorithm is more accurate at determining personality traits based on selfie photographs than humans are.
