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Have you ever misremembered an event, while being totally certain it actually happened? Most people have experienced the unreliability of human memory. As it turns out, false memories are very easy to generate. Scientists at the Riken–MIT Center for Neural Circuit Genetics have created false memories in mice using a procedure they say would also work for humans.

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This article was originally posted on The Astronauts blog.

Story-telling games need player’s empathy to work, and yet we rarely have any discussion about it.

Not that I was even aware of the problem until recently. It all changed when I finished Beyond: Two Souls, posted a blog piece, and this question appeared on my Twitter feed:

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Original author: 
John Timmer

elliottzone

One of the problems with cognitive and behavioral research is getting a good cross-section of the general population. Although they're convenient to work with, a couple hundred college students rarely represent the full diversity of human capability and behavior, yet that's exactly what many studies rely on. But a brain-training game may now provide access to data on scales that behavioral scientists probably never dreamed of. With a user base of over 35 million, the data obtained through the game could help us tease out very subtle effects. But as a start, a team of researchers have focused on some simpler questions: how aging and alcohol affect our ability to learn.

The software is less a game itself than a game and survey platform. Developed by a company called Lumosity, it's available on mobile platforms and through a Web interface. The platform can run a variety of games (a typical one asks users to answer math questions that appear in raindrops before they hit the ground), all with an emphasis on brain training. A few games are available for free and users can pay to get access to more advanced ones.

The scientific literature on brain training games is a bit mixed, and there's some controversy about whether the games improve mental function in general, or only those specific areas of cognition that the game focuses on. Lumosity clearly argues for the former and one of its employees pointed Ars to a number of studies that he felt validate the company's approach. What's not in doubt, however, is that it has a huge user base with over 35 million registered users. And because the Lumosity platform is flexible, it has been able to get basic demographic information from many of those users; they and others have also filled out personality profiles and other assessments.

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Original author: 
Ben Popper

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The field of neuroscience has been animated recently by the use of Functional Magnetic Resonance Imaging, or fMRI. When a person lies in an fMRI machine, scientists can see their brain activity in real time. It’s a species of mind reading that promises to unlock the still mysterious workings of our grey matter.

In April, a team in Japan announced that they could identify when a subject was dreaming about different types of objects like a house, a clock, or a husband. Last November, another group of researchers using this technique was able to predict if gadget columnist David Pogue was thinking about a skyscraper or a strawberry.

What earlier studies couldn’t determine, however, was how the subjects were actually feeling. A new...

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Indigenous Healer

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Original author: 
Soulskill

An anonymous reader writes "We're seeing a new revolution in artificial intelligence known as deep learning: algorithms modeled after the brain have made amazing strides and have been consistently winning both industrial and academic data competitions with minimal effort. 'Basically, it involves building neural networks — networks that mimic the behavior of the human brain. Much like the brain, these multi-layered computer networks can gather information and react to it. They can build up an understanding of what objects look or sound like. In an effort to recreate human vision, for example, you might build a basic layer of artificial neurons that can detect simple things like the edges of a particular shape. The next layer could then piece together these edges to identify the larger shape, and then the shapes could be strung together to understand an object. The key here is that the software does all this on its own — a big advantage over older AI models, which required engineers to massage the visual or auditory data so that it could be digested by the machine-learning algorithm.' Are we ready to blur the line between hardware and wetware?"

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Young girls from the Krobo tribal group wear traditional beads
the dipo ceremony of the krobo girls in ghana, the transition from girls who become women, mothers and wives.

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(author unknown)

doublenifty:

Some inspiring and helpful thoughts on the creative career by our good man Ze Frank.

Some salient points in there about business and education as well.

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