Interestingly, despite the large number of nodes
in our brain network data, the number of major modules did not change dramatically from the previously reported brain network modularity [9]--[13], [29].
Not exact matches
A neural
network is made of layers of small computing elements that process
data in a way reminiscent of the
brain's neurons.
Artificial neural
networks, computer programs that mimic the human
brain, are great at learning patterns and sequences, but so far they've been limited
in their ability to solve complex reasoning problems that require storing and manipulating lots of
data.
While the
data showed that regions across the
brain were involved
in creative thought, Beaty said the evidence pointed to three subnetworks — the default mode
network, the salience
network and the executive control
network — that appear to play key roles
in creative thought.
Beaty and colleagues reanalyzed
brain data from previous studies and found that, by simply measuring the strength of connections
in these peoples»
brain networks, they could estimate how original their ideas would be.
An international team of roughly 300 scientists known as the Enhancing Neuro Imaging Genetics through Meta Analysis (ENIGMA)
Network pooled
brain scans and genetic
data worldwide to pinpoint genes that enhance or break down key
brain regions
in people from 33 countries.
Studies suggest that computer models called neural
networks may learn to recognize patterns
in data using the same algorithms as the human
brain
Machine - learning systems — and a subset, deep - learning systems, which simulate complex neural
networks in the human
brain — derive their own rules after combing through large amounts of
data.
Christopher Shallue of Google and Andrew Vanderburg at the University of Texas at Austin used a neural
network — a type of machine learning that mimics the connections
in a
brain — to look for new planets
in old Kepler
data.
The researchers, who published their work
in Cell today (April 12), designed their a neural
network, a program modeled after the
brain, using an approach called deep learning, which uses
data to recognize patterns, form rules, and apply those rules to new information.
She uses a new ultra-fast microscopy technique to record the activity
in the whole fly
brain and works closely with theoretical neuroscientists to analyze the
data and model
network activity.
From the descriptive view on the
data it seems that compared to sham, verum acupuncture tended to be associated with more activation
in the basal ganglia,
brain stem, cerebellum, and insula and more deactivation was seen
in the so - called «default mode
network» and limbic
brain areas, such as the amygdala and the hippocampus.
Based on our synthesis of published anatomical and functional
data in humans and nonhuman animals (see Materials and Methods), we hypothesized that the amygdala would parse into three subregions that each anchor a large - scale
network of
brain regions implicated
in distinct processes of social cognition.