miércoles, 16 de septiembre de 2009
sk-interfaces
Skin is our natural interface to the world – but it is progressively being replaced by technological extensions, some of which can have liberating, other rather new restrictive, effects. The trans-disciplinary exhibition sk-interfaces presents about 20 international artists who question the ways in which today’s techno-sciences alter our relation to the world: digital technologies, architecture, tissue cultures, transgenesis, self-experiments or telepresence – the artists appropriate these methods and explore the permeability between disciplines and between art and science. Their interfaces connect us with different species, destabilise our definition of being human today and reflect on the question of satellite bodies.
sábado, 5 de septiembre de 2009
Migraine: Is acupuncture clinically viable for treating acute migraine?
Chinese investigators performed a well-designed, randomized trial to investigate the efficacy of true Chinese acupuncture compared with two different sham acupuncture approaches for the treatment of acute migraine attacks. Real acupuncture was superior to sham acupuncture, but the absolute pain relief was minimal.
lunes, 24 de agosto de 2009
Musicología y "Biosubjetividades": algunas coordenadas
Acostumbrados a unas "ciencias de la música" centradas en el historicismo, los catálogos, archivos y "biobibliografías", olvidamos que la Musicología es una de las disciplinas más eclécticas y fascinantes: ciencia humana y social, estudio cultural, reto intelectual y creativo. Quizás porque los "académicos" suelen imponer sus limitaciones a la propia ciencia que dicen practicar, en pos de la denominada "objetividad comunitaria" (*). Por esta razón les invito a conocer la colección Ashgate Contemporary Thinkers, que actualmente incluye ensayos críticos de algunas de las mentes más brillantes de la musicología crítica anglosajona.
En esta línea, quisiera recomendar un libro que se ubica justo en el limes entre Musicología crítica y Biosubjetividades, un ensayo de "musicología carnal": Boccherini's Body: An Essay in Carnal Musicology de Elisabeth Le Guin.
ESPERO MOTIVARLES CON ESTAS BREVÍSIMAS COORDENADAS...
_____________
* A los(as) que se sientan provocados(as) por esta propuesta les recomiendo: Daston, L., & Peter Galison, P. (2007). Objectivity. New York: Zone Books
Functional neural network analysis in frontotemporal dementia and Alzheimer's disease using EEG and graph theory
Willem de Haan, Yolande A L Pijnenburg, Rob L M Strijers, Yolande van der Made, Wiesje M van der Flier, Philip Scheltens and Cornelis J Stam.
Background
Although a large body of knowledge about both brain structure and function has been gathered over the last decades, we still have a poor understanding of their exact relationship. Graph theory provides a method to study the relation between network structure and function, and its application to neuroscientific data is an emerging research field. We investigated topological changes in large-scale functional brain networks in patients with Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD) by means of graph theoretical analysis of resting-state EEG recordings. EEGs of 20 patients with mild to moderate AD, 15 FTLD patients, and 23 non-demented individuals were recorded in an eyes-closed resting-state. The synchronization likelihood (SL), a measure of functional connectivity, was calculated for each sensor pair in 0.5-4 Hz, 4-8 Hz, 8-10 Hz, 10-13 Hz, 13-30 Hz and 30-45 Hz frequency bands. The resulting connectivity matrices were converted to unweighted graphs, whose structure was characterized with several measures: mean clustering coefficient (local connectivity), characteristic path length (global connectivity ) and degree correlation (network 'assortativity'). All results were normalized for network size and compared with random control networks.
Results
In AD, the clustering coefficient decreased in the lower alpha and beta bands (p<0.001) and the characteristic path length decreased in the lower alpha and gamma bands (p<0.05) compared to controls. Although there was a constant trend towards increase, in FTLD no significant differences with controls were found using these measures. The degree correlation decreased in both alpha bands in AD compared to controls (p<0.05), but increased in the FTLD lower alpha band compared with controls (p <0.01).
Conclusions
With decreasing local and global connectivity parameters, the large-scale functional brain network organization in AD deviates from the optimal 'small-world' network structure towards a more 'random' type. This is associated with less efficient information exchange between brain areas, supporting the disconnection hypothesis of AD. Surprisingly, FTLD patients show changes in the opposite direction, towards a (perhaps excessively) more 'ordered' network structure, possibly reflecting a different underlying pathophysiological process. Our results suggest that graph theory applied to neurophysiologic data is a promising method to study functional brain changes in dementia, and it might contribute to bridging the gap in our knowledge about the relation between brain damage and cognitive dysfunction.
The complete
Background
Although a large body of knowledge about both brain structure and function has been gathered over the last decades, we still have a poor understanding of their exact relationship. Graph theory provides a method to study the relation between network structure and function, and its application to neuroscientific data is an emerging research field. We investigated topological changes in large-scale functional brain networks in patients with Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD) by means of graph theoretical analysis of resting-state EEG recordings. EEGs of 20 patients with mild to moderate AD, 15 FTLD patients, and 23 non-demented individuals were recorded in an eyes-closed resting-state. The synchronization likelihood (SL), a measure of functional connectivity, was calculated for each sensor pair in 0.5-4 Hz, 4-8 Hz, 8-10 Hz, 10-13 Hz, 13-30 Hz and 30-45 Hz frequency bands. The resulting connectivity matrices were converted to unweighted graphs, whose structure was characterized with several measures: mean clustering coefficient (local connectivity), characteristic path length (global connectivity ) and degree correlation (network 'assortativity'). All results were normalized for network size and compared with random control networks.
Results
In AD, the clustering coefficient decreased in the lower alpha and beta bands (p<0.001) and the characteristic path length decreased in the lower alpha and gamma bands (p<0.05) compared to controls. Although there was a constant trend towards increase, in FTLD no significant differences with controls were found using these measures. The degree correlation decreased in both alpha bands in AD compared to controls (p<0.05), but increased in the FTLD lower alpha band compared with controls (p <0.01).
Conclusions
With decreasing local and global connectivity parameters, the large-scale functional brain network organization in AD deviates from the optimal 'small-world' network structure towards a more 'random' type. This is associated with less efficient information exchange between brain areas, supporting the disconnection hypothesis of AD. Surprisingly, FTLD patients show changes in the opposite direction, towards a (perhaps excessively) more 'ordered' network structure, possibly reflecting a different underlying pathophysiological process. Our results suggest that graph theory applied to neurophysiologic data is a promising method to study functional brain changes in dementia, and it might contribute to bridging the gap in our knowledge about the relation between brain damage and cognitive dysfunction.
The complete
martes, 14 de julio de 2009
The Next Hacking Frontier: Your Brain?
By Hadley Leggett
Hackers who commandeer your computer are bad enough. Now scientists worry that someday, they’ll try to take over your brain.
In the past year, researchers have developed technology that makes it possible to use thoughts to operate a computer, maneuver a wheelchair or even use Twitter — all without lifting a finger. But as neural devices become more complicated — and go wireless — some scientists say the risks of “brain hacking” should be taken seriously.
“Neural devices are innovating at an extremely rapid rate and hold tremendous promise for the future,” said computer security expert Tadayoshi Kohno of the University of Washington. “But if we don’t start paying attention to security, we’re worried that we might find ourselves in five or 10 years saying we’ve made a big mistake.”
Hackers tap into personal computers all the time — but what would happen if they focused their nefarious energy on neural devices, such as the deep-brain stimulators currently used to treat Parkinson’s and depression, or electrode systems for controlling prosthetic limbs? According to Kohno and his colleagues, who published their concerns July 1 in Neurosurgical Focus, most current devices carry few security risks. But as neural engineering becomes more complex and more widespread, the potential for security breaches will mushroom.
For example, the next generation of implantable devices to control prosthetic limbs will likely include wireless controls that allow physicians to remotely adjust settings on the machine. If neural engineers don’t build in security features such as encryption and access control, an attacker could hijack the device and take over the robotic limb.
“It’s very hard to design complex systems that don’t have bugs,” Kohno said. “As these medical devices start to become more and more complicated, it gets easier and easier for people to overlook a bug that could become a very serious risk. It might border on science fiction today, but so did going to the moon 50 years ago.”
Some might question why anyone would want to hack into someone else’s brain, but the researchers say there’s a precedent for using computers to cause neurological harm. In November 2007 and March 2008, malicious programmers vandalized epilepsy support websites by putting up flashing animations, which caused seizures in some photo-sensitive patients.
“It happened on two separate occasions,” said computer science graduate student Tamara Denning, a co-author on the paper. “It’s evidence that people will be malicious and try to compromise peoples’ health using computers, especially if neural devices become more widespread.”
In some cases, patients might even want to hack into their own neural device. Unlike devices to control prosthetic limbs, which still use wires, many deep brain stimulators already rely on wireless signals. Hacking into these devices could enable patients to “self-prescribe” elevated moods or pain relief by increasing the activity of the brain’s reward centers.
Despite the risks, Kohno said, most new devices aren’t created with security in mind. Neural engineers carefully consider the safety and reliability of new equipment, and neuroethicists focus on whether a new device fits ethical guidelines. But until now, few groups have considered how neural devices might be hijacked to perform unintended actions. This is the first time an academic paper has addressed the topic of “neurosecurity,” a term the group coined to describe their field.
“The security and privacy issues somehow seem to slip by,” Kohno said. “I would not be surprised if most people working in this space have never thought about security.”
Kevin Otto, a bioengineer who studies brain-machine interfaces at Purdue Universty, said he was initially skeptical of the research. “When I first picked up the paper, I don’t know if I agreed that it was an issue. But the paper gives a very compelling argument that this is important, and that this is the time to have neural engineers collaborate with security developers.”
It’s never too early to start thinking about security issues, said neural engineer Justin Williams of the University of Wisconsin, who was not involved in the research. But he stressed that the kinds of devices available today are not susceptible to attack, and that fear of future risks shouldn’t impede progress in the field. “These kinds of security issues have to proceed in lockstep with the technology,” Williams said.
History provides plenty of examples of why it’s important to think about security before it becomes a problem, Kohno said. Perhaps the best example is the internet, which was originally conceived as a research project and didn’t take security into account.
“Because the internet was not originally designed with security in mind,” the researchers wrote, “it is incredibly challenging — if not impossible — to retrofit the existing internet infrastructure to meet all of today’s security goals.” Kohno and his colleagues hope to avoid such problems in the neural device world, by getting the community to discuss potential security problems before they become a reality.
“The first thing is to ask ourselves is, ‘Could there be a security and privacy problem?’” Kohno said. “Asking ‘Is there a problem?’ gets you 90 percent there, and that’s the most important thing.”
Hackers who commandeer your computer are bad enough. Now scientists worry that someday, they’ll try to take over your brain.
In the past year, researchers have developed technology that makes it possible to use thoughts to operate a computer, maneuver a wheelchair or even use Twitter — all without lifting a finger. But as neural devices become more complicated — and go wireless — some scientists say the risks of “brain hacking” should be taken seriously.
“Neural devices are innovating at an extremely rapid rate and hold tremendous promise for the future,” said computer security expert Tadayoshi Kohno of the University of Washington. “But if we don’t start paying attention to security, we’re worried that we might find ourselves in five or 10 years saying we’ve made a big mistake.”
Hackers tap into personal computers all the time — but what would happen if they focused their nefarious energy on neural devices, such as the deep-brain stimulators currently used to treat Parkinson’s and depression, or electrode systems for controlling prosthetic limbs? According to Kohno and his colleagues, who published their concerns July 1 in Neurosurgical Focus, most current devices carry few security risks. But as neural engineering becomes more complex and more widespread, the potential for security breaches will mushroom.
For example, the next generation of implantable devices to control prosthetic limbs will likely include wireless controls that allow physicians to remotely adjust settings on the machine. If neural engineers don’t build in security features such as encryption and access control, an attacker could hijack the device and take over the robotic limb.
“It’s very hard to design complex systems that don’t have bugs,” Kohno said. “As these medical devices start to become more and more complicated, it gets easier and easier for people to overlook a bug that could become a very serious risk. It might border on science fiction today, but so did going to the moon 50 years ago.”
Some might question why anyone would want to hack into someone else’s brain, but the researchers say there’s a precedent for using computers to cause neurological harm. In November 2007 and March 2008, malicious programmers vandalized epilepsy support websites by putting up flashing animations, which caused seizures in some photo-sensitive patients.
“It happened on two separate occasions,” said computer science graduate student Tamara Denning, a co-author on the paper. “It’s evidence that people will be malicious and try to compromise peoples’ health using computers, especially if neural devices become more widespread.”
In some cases, patients might even want to hack into their own neural device. Unlike devices to control prosthetic limbs, which still use wires, many deep brain stimulators already rely on wireless signals. Hacking into these devices could enable patients to “self-prescribe” elevated moods or pain relief by increasing the activity of the brain’s reward centers.
Despite the risks, Kohno said, most new devices aren’t created with security in mind. Neural engineers carefully consider the safety and reliability of new equipment, and neuroethicists focus on whether a new device fits ethical guidelines. But until now, few groups have considered how neural devices might be hijacked to perform unintended actions. This is the first time an academic paper has addressed the topic of “neurosecurity,” a term the group coined to describe their field.
“The security and privacy issues somehow seem to slip by,” Kohno said. “I would not be surprised if most people working in this space have never thought about security.”
Kevin Otto, a bioengineer who studies brain-machine interfaces at Purdue Universty, said he was initially skeptical of the research. “When I first picked up the paper, I don’t know if I agreed that it was an issue. But the paper gives a very compelling argument that this is important, and that this is the time to have neural engineers collaborate with security developers.”
It’s never too early to start thinking about security issues, said neural engineer Justin Williams of the University of Wisconsin, who was not involved in the research. But he stressed that the kinds of devices available today are not susceptible to attack, and that fear of future risks shouldn’t impede progress in the field. “These kinds of security issues have to proceed in lockstep with the technology,” Williams said.
History provides plenty of examples of why it’s important to think about security before it becomes a problem, Kohno said. Perhaps the best example is the internet, which was originally conceived as a research project and didn’t take security into account.
“Because the internet was not originally designed with security in mind,” the researchers wrote, “it is incredibly challenging — if not impossible — to retrofit the existing internet infrastructure to meet all of today’s security goals.” Kohno and his colleagues hope to avoid such problems in the neural device world, by getting the community to discuss potential security problems before they become a reality.
“The first thing is to ask ourselves is, ‘Could there be a security and privacy problem?’” Kohno said. “Asking ‘Is there a problem?’ gets you 90 percent there, and that’s the most important thing.”
martes, 7 de julio de 2009
Eavesdropping on the music of the brain
by Nora Schultz
06 July 2009
New Scientist
WHAT does the human brain sound like? Now you can find out thanks to a technique for turning its flickering activity into music. Listening to scans may also give new insights into the differences and similarities between normal and dysfunctional brains.
Brain scans created using functional MRI consist of a series of images in which different areas light up with varying intensity at different times. These can be used to determine which parts of the brain are active during a particular task.
To turn such scans into music, philosopher Dan Lloyd at Trinity College in Hartford, Connecticut, identified regions that become active together and assigned each of these groups a different pitch. He then created software that analyses a series of scans and generates the notes at these pitches as the corresponding brain areas light up. Each note is played at a volume that corresponds to the intensity of activity.
When Lloyd fed the software a set of scans of his own brain taken as he switched between driving a virtual-reality car and resting, he found that he could detect the switch-over in the sounds.
Lloyd then gave the software scans taken from volunteers with dementia and schizophrenia, and from healthy volunteers. The brains of people with schizophrenia switched between low and high activity more erratically than healthy brains, allowing the two types of brain to be distinguished by sound alone.
While this difference is also clear from looking at the images, Lloyd's collaborator Vince Calhoun at the University of New Mexico in Albuquerque, says there are variations in the music from people with schizophrenia that are not visually obvious. "It almost sounds like there is more background warbling," he says.
He suggests that these "unsteady rhythms and cadences" may be indicative of dysfunction in the brain. Lloyd also identified sounds and rhythms in the brains of people with dementia that distinguished them from healthy volunteers.
Could identifying such aural differences ever be useful? Daniel Levitin, a neuroscientist at McGill University in Montreal, Canada, thinks they might. He says brain music's killer application might be in allowing researchers to home in on patterns that suggest a particular region is interesting and that wouldn't be detectable using the eye alone. They could analyse these regions more closely using conventional imaging.
His colleague Didier Grandjean at the University of Geneva in Switzerland says that brain music might help identify temporal patterns in particular. "Melodies are a much better way to build complex mental representations over time than anything the eye can do," he says.
Lloyd is also keen to explore the aesthetic aspects of brain music. "It's not quite like composed sound but it's not random either, it's 'almost music'. My students are putting it on their playlists."
06 July 2009
New Scientist
WHAT does the human brain sound like? Now you can find out thanks to a technique for turning its flickering activity into music. Listening to scans may also give new insights into the differences and similarities between normal and dysfunctional brains.
Brain scans created using functional MRI consist of a series of images in which different areas light up with varying intensity at different times. These can be used to determine which parts of the brain are active during a particular task.
To turn such scans into music, philosopher Dan Lloyd at Trinity College in Hartford, Connecticut, identified regions that become active together and assigned each of these groups a different pitch. He then created software that analyses a series of scans and generates the notes at these pitches as the corresponding brain areas light up. Each note is played at a volume that corresponds to the intensity of activity.
When Lloyd fed the software a set of scans of his own brain taken as he switched between driving a virtual-reality car and resting, he found that he could detect the switch-over in the sounds.
Lloyd then gave the software scans taken from volunteers with dementia and schizophrenia, and from healthy volunteers. The brains of people with schizophrenia switched between low and high activity more erratically than healthy brains, allowing the two types of brain to be distinguished by sound alone.
While this difference is also clear from looking at the images, Lloyd's collaborator Vince Calhoun at the University of New Mexico in Albuquerque, says there are variations in the music from people with schizophrenia that are not visually obvious. "It almost sounds like there is more background warbling," he says.
He suggests that these "unsteady rhythms and cadences" may be indicative of dysfunction in the brain. Lloyd also identified sounds and rhythms in the brains of people with dementia that distinguished them from healthy volunteers.
Could identifying such aural differences ever be useful? Daniel Levitin, a neuroscientist at McGill University in Montreal, Canada, thinks they might. He says brain music's killer application might be in allowing researchers to home in on patterns that suggest a particular region is interesting and that wouldn't be detectable using the eye alone. They could analyse these regions more closely using conventional imaging.
His colleague Didier Grandjean at the University of Geneva in Switzerland says that brain music might help identify temporal patterns in particular. "Melodies are a much better way to build complex mental representations over time than anything the eye can do," he says.
Lloyd is also keen to explore the aesthetic aspects of brain music. "It's not quite like composed sound but it's not random either, it's 'almost music'. My students are putting it on their playlists."
Suscribirse a:
Entradas (Atom)
