The ability of animals and humans to infer and apply new rules in order to maximize success relies on frontal lobes. Recent study indicates that in neural dynamics, roups of frontal cortex neurons in rat brains switch from encoding a familiar rule to a completely novel rule that could only be deduced from trail and error. The research also focused on the behaviour of the neurons when adapting to the new activity.
Reference: Science Daily
Showing posts with label Neural network. Show all posts
Showing posts with label Neural network. Show all posts
5/14/10
4/30/10
Observing Brain in the Act of Seeing
Neuroscientists have shown that individual neurons carry out significant aspects of sensory processing. The method allows for the first time to observe individual synapses, small differences between nerve contact sites.
Reference: Science Daily
Reference: Science Daily
Labels:
brain,
human biology,
Neural network,
processes
1/7/10
Altered Perception of Hands
The space within reach with our hands is named "action space". Research has shown that visual information in this area is organized in hand-centered coordinates, representation of objects in the human brain depends on their physical location with respect to the hand. New research shows that amputation of the hand results in distorted visuospatial perception.
Reference:
Amputees %u2018Neglect%u2019 the Space Near Their Missing Hand. Psychological Science, January 2010
Reference:
Amputees %u2018Neglect%u2019 the Space Near Their Missing Hand. Psychological Science, January 2010
Labels:
brain,
disability,
Neural network
1/4/10
Scans Show Learning 'Scripts' the Brain's Connections
Spontaneous brain activity formerly thought to be "white noise" is subject to change after an individual learns a new task. Scientists report that the degree of change reflects how well subjects have learned to perform the task. Even during sleep or anesthesia, the brain's spontaneous activity is not random, but organized patterns of correlated activity that occur in anatomically and functionally connected regions.
Reference:
Lewis et al. Learning sculpts the spontaneous activity of the resting human brain. Proceedings of the National Academy of Sciences, 2009; DOI: 10.1073/pnas.0902455106
Reference:
Lewis et al. Learning sculpts the spontaneous activity of the resting human brain. Proceedings of the National Academy of Sciences, 2009; DOI: 10.1073/pnas.0902455106
Labels:
brain,
cognitive psychology,
learning,
network,
Neural network
10/28/09
Brain-Machine Interface Research
Brain-computing with a prosthetic device is gaining ground on research and development. Researchers at Duke University Medical Center is working on a real-time interface with a full-body exoskeleton to be controlled by signals from a paraplegics brain. Their ultimate goal is to enable a paralyzed individual to walk again by the end of 2012.
Four years ago, the project began with the implantation of electrodes in a rhesus monkey's brain that detects the movement of an arm. The initial process is decoding the brain signals from the monkey's cerebral cortex while it held a joystick to move a single shape in a video game. Eventually, the monkey was able to use its mind to move the object without the joystick. Three years later, a different rhesus monkey was implanted with a new BMI in the motor and sensory cortex to control a computer-screen image of a human-like figure walking on treadmill. The monkey was rewarded for walking in sync with the robot. The treadmill was turned off after an hour, but the monkey was able to direct the robot to walk another few minutes. This research indicates that part of the monkey's brain is adapted to control the robot movement. Therefore it is possible to establish connections between the brain and a computational device, which will lead to the ability to control the movement of limbs.
Reference: IEEE Institute
Labels:
autonomous robots,
brain,
locomotion,
Neural network
9/22/09
Fostering Creativity in Problem Solving
Discoveries and insights on the frontiers of science do not come from thin air but emerges from incremental processes of weaving together analogies, images and simulations. Scientists built real-world models and make predictions from them. They study the cognitive process by observing scientists at work in the lab. The study can help foster improved creativity in labs and allow students to model-based reasoning approaches to problem solving.
Reference: Science Daily
Labels:
cognitive science,
learning,
Neural network
9/21/09
Learning for Individuals in Vegetative States
Scientists, for the first time, tested that patients in vegetative and minimally conscious states can learn. After training, patients would start to blink when the tone played but before the air puff to the eye. The classical conditioning in the vegetative and minimally conscious state will be published in the Advanced Online Publication of Nature Neuroscience.
Reference: Science Daily
Labels:
cognitive science,
learning,
medical imaging,
Neural network,
vegetative
8/30/09
Visualization of Simulated Brain
For the first time, scientists are able to see the brain electrically prodded at the cellular level. For years, electrical stimulation has been used to treat the human brain and has helped identify regions responsible for specific neural functions. Originally it is difficult to measure the small currents produced by neurons due to the high voltages applied to stimulate the brain. The solution is a new form of optical imaging called two-photon microscopy, tracking calcium levels of neurons. Since calcium levels spike every time a neuron fires, the team could monitor which neurons were being triggered.
Interestingly, neural response to electrical currents isn't localized and not all neurons surrounding an electrode fire at once. These findings will appear in the August 27 issue of "Neuron".
Reference: Science Daily
Labels:
brain,
Neural network,
optics
8/18/09
Evolutionary Robots Gain Powers of Deception
Researches in Switzerland have found that robots equiped with artificial neural networks can develop the ability to decieve under guidence of simple regulations.
The robots are programed to seek out food and they learned to conceal their visual signals from other robots to keep the food for themselves. The team made generations of these robots by combining the AI neural networks of the most successful robots. A few random changes in code models the idea of biological mutations. Interestingly, after 100 generations the robots stopped flashing light when they are near food and evolved to attract or repelled by light. Due to the competition for food, the robots try to conceal information that gives it away.
This research can further our understanding of biological communication systems.
Reference: Kristina Grifantini ~ Technology Review.com
The robots are programed to seek out food and they learned to conceal their visual signals from other robots to keep the food for themselves. The team made generations of these robots by combining the AI neural networks of the most successful robots. A few random changes in code models the idea of biological mutations. Interestingly, after 100 generations the robots stopped flashing light when they are near food and evolved to attract or repelled by light. Due to the competition for food, the robots try to conceal information that gives it away.
This research can further our understanding of biological communication systems.
Reference: Kristina Grifantini ~ Technology Review.com
Labels:
AI,
Neural network,
robots
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