In vitro biological neural networks (BNNs) embodied in robots exhibit a wide range of complex behaviors, including supervised and unsupervised learning, memory, object tracking, obstacle avoidance, and the ability to play simple games.
Utilizing a classic neural network, researchers have created a new artificial intelligence model based on recent biological findings that shows improved memory performance.
Researchers explain how deep neural networks are able to learn complex physics.
Adults and children as young as 4 utilize the same neural network, the multiple demand network, to help solve difficult cognitive problems. The findings demonstrate this important network for problem-solving and attention develops early in life.
Alterations in the cerebral neural network could function as a biomarker for the early diagnosis of mild cognitive impairment, Alzheimer's disease, and Lewy Body dementia.
A new software framework incorporates dendritic properties and mechanisms into large-scale neural network models.
A new brain mapping study reveals a neural network in cuttlefish that involves chemosensory function and body pattern control which the cuttlefish utilize for foraging and camouflage.
One-minute stimulation with monochromatic light activates several visual and non-visual brain regions. The findings shed light on the impact of light stimulation on brain function.
Feed-forward neural networks improve speed and provide more accurate control of brain-controlled prosthetic hands and fingers.
Treatments for depression including ECT and antidepressants increase brain connectivity in those with clinical depression.
Study reveals a hidden order in seemingly random connections between neurons.
Neural silencing periods are not a disadvantage representing biological limitations, but rather an advantage for temporal sequencing identification.
