* ...

About This Page

This is a Techmeme archive page. It shows how the site appeared at 8:20 PM ET, January 27, 2012.

The most current version of the site as always is available at our home page. To view an earlier snapshot click here and then modify the date indicated.

From Mediagazer

Tim Castle / Reuters:

UK police arrest Murdoch tabloid staff

Laura Hazard Owen / paidContent:

As Goodreads Ends Sourcing From Amazon, Users Fear Lost Books

Amy Chozick / Media Decoder:

Bloomberg Executive Is Said to Be in Talks to Lead Dow Jones

I'm coming to the APPs game quite late in a career that started with BIG iron back in the 1960s, but I just have to admit that I'm really impressed by the potential promise of "device" computing.

I believe this has enormous potential, especially in combination with other such new (e.g. nanotechnology) developments.

Just a personal "bookmark" (at least for the moment) that is part of my current review of the way I have been using posterous.

A fascinating extension of the "toolbox".

Predictors of face-selective regions are labeled from red to yellow, and scene-selective predictors are labeled from blue to light blue. The seed region is highlighted in purple. (Credit: Zeynep M Saygin et al./Nature Neuroscience)

For more than a decade, neuroscientists have known that many of the cells in a brain region called the fusiform gyrus specialize in recognizing faces. However, those cells don’t act alone: They need to communicate with several other parts of the brain. By tracing those connections, MIT neuroscientists have now shown that they can accurately predict which parts of the fusiform gyrus are face-selective.

This approach may allow scientists to learn more about the face-recognition impairments often seen in autism and prosopagnosia, a disorder often caused by stroke. It could also be used to determine relationships between structure and function in other parts of the brain.

The study is the first to link a brain region’s connectivity with its function. No two people have the exact same fusiform gyrus structure, but using connectivity patterns, the researchers can now accurately predict which parts of an individual’s fusiform gyrus are involved in face recognition.

To map the brain’s connectivity patterns, the researchers used a technique called diffusion-weighted imaging, which is based on MRI. A magnetic field applied to the brain of the person in the scanner causes water in the brain to flow in the same direction. However, wherever there are axons — the long cellular extensions that connect a neuron to other brain regions — water is forced to flow along the axon, rather than crossing it. This is because axons are coated in a fatty material called myelin, which is impervious to water.

By applying the magnetic field in many different directions and observing which way the water flows, the researchers can identify the locations of axons and determine which brain regions they are connecting.

Making connections

The researchers found that certain patches of the fusiform gyrus were strongly connected to brain regions also known to be involved in face recognition, including the superior and inferior temporal cortices. Those fusiform gyrus patches were also most active when the subjects were performing face-recognition tasks.

Based on the results in one group of subjects, the researchers created a model that predicts function in the fusiform gyrus based solely on the observed connectivity patterns. In a second group of subjects, they found that the model successfully predicted which patches of the fusiform gyrus would respond to faces.

The other regions connected to the fusiform gyrus are believed to be involved in higher-level visual processing. One surprise was that some parts of the fusiform gyrus connect to a part of the brain called the cerebellar cortex, which is not thought to be part of the traditional vision-processing pathway. That area has not been studied very thoroughly, but a few studies have suggested that it might have a role in face recognition.

Now that the researchers have an accurate model to predict function of fusiform gyrus cells based solely on their connectivity, they could use the model to study the brains of patients, such as severely autistic children, who can’t lie down in an MRI scanner long enough to participate in a series of face-recognition tasks. That is one of the most important aspects of the study, says Michael Beauchamp, an associate professor of neurobiology at the University of Texas Medical School.

The MIT researchers are now expanding their connectivity studies into other brain regions and other visual functions, such as recognizing objects and scenes, as well as faces. They hope that such studies will also help to reveal some of the mechanisms of how information is processed at each point as it flows through the brain.

Ref.: Zeynep M Saygin et al., Anatomical connectivity patterns predict face selectivity in the fusiform gyrus, Nature Neuroscience, 2011, [doi: 10.1038/nn.3001]

Fascinating!

This remains a favorite site that I keep coming back to in spite of the fact that its been around for quite a while.