The Myth of the Scientist: Crystal Dilworth at TEDxYouth@Caltech
Scientists don’t fit the stereotypical mold some people think they do. It doesn’t take much to replace those views. The main point, in my opinion, is to let kids know they can be a scientists even if they are not like the stereotypical examples – though it will take a lot of work.
[Jonathan Grainger, researcher, Aix-Marseille University] says a baboon named Dan learned more than 300 words. “Dan’s our star baboon,” he says. “He’s a high-performing individual, basically. He does well in most tasks.”
But here’s the amazing thing: Dan and the other baboons also learned to tell whether a string of letters they’d never seen before was an English word. That’s something first-graders learn to do when they start reading, but scientists had assumed that children were simply sounding out the letters to decide whether they make sense.
Of course, the baboons couldn’t do this because they’re not learning to read a language they already speak. They had to rely on a part of the brain that can tell whether objects fit a known pattern.
Michael Platt, who directs the Duke Institute for Brain Sciences, says he was surprised by what the baboons were able to do.
“I was really looking for holes to poke in this study, but it was very difficult to find any because it was really beautifully done,” he says. “And I think the linchpin here was that the baboons, once they had learned the rule, could generalize to new words that they had not seen before.”
Platt says when you think about it, the finding makes sense, given what’s known about human and animal brains. “Brains are always looking for patterns,” he says. “They are always looking to make some statistical pattern analysis of the features and events that are in the environment. And this would just be one of those.”
Platt says that’s a big departure from the idea that reading is a direct extension of spoken language.
One questions I have, is why the experiment done in France tested wether the Baboons could recognize English words?
I find these kind of stories so interesting. I really have so little understanding of genes. I knew memory had something to do with altering connections between neurons. I had no idea that required turning on many genes in those neurons. Life really is amazing.
When you experience a new event, your brain encodes a memory of it by altering the connections between neurons. This requires turning on many genes in those neurons.
Lin and her colleagues found that Npas4 turns on a series of other genes that modify the brain’s internal wiring by adjusting the strength of synapses, or connections between neurons. “This is a gene that can connect from experience to the eventual changing of the circuit,” says [Yingxi] Lin
So far, the researchers have identified only a few of the genes regulated by Npas4, but they suspect there could be hundreds more. Npas4 is a transcription factor, meaning it controls the copying of other genes into messenger RNA — the genetic material that carries protein-building instructions from the nucleus to the rest of the cell. The MIT experiments showed that Npas4 binds to the activation sites of specific genes and directs an enzyme called RNA polymerase II to start copying them.
“Npas4 is providing this instructive signal,” Ramamoorthi says. “It’s telling the polymerase to land at certain genes, and without it, the polymerase doesn’t know where to go. It’s just floating around in the nucleus.”
When the researchers knocked out the gene for Npas4, they found that mice could not remember their fearful conditioning. They also found that this effect could be produced by knocking out the gene just in the CA3 region of the hippocampus. Knocking it out in other parts of the hippocampus, however, had no effect.
One of the things I aim to do in 2012 is read a few more books on biology and genes. I find it incredible what are genes actually are doing to allow us to live our lives. And I am also very ignorant on the whole area. So hopefully I can have some fun next year learning about it.
This idea is a bit scary to me, the self driving car is less so. But it is great to see us pushing the engineering boundaries forward. It is such a shame that the huge economic failures in the USA, Europe and Japan are rightly grabbing much of the attention these days. If we just reduced the waste and corruption in the political and financial systems it would allow us to take more joy is the great time we do for awesome engineering breakthroughs. Still, if we can try to block out those painful economic realities, these types of breakthroughs are really cool.
The webcast shows the work of the Artificial Intelligence Group of the Freie Universität Berlin in Germany (BrainDriver).
And Nissan is collaborating with the École Polytechnique Fédérale de Lausanne in Switzerland (EPFL) on a car that uses your brain signals (along with signals the computer gets via its own sensors) to aid in driving. Continue reading →
the two physically identical tiles do indeed now look very different.
Why? The information in the image strongly suggests that the dark brown tile on the top now means a poorly reflective surface under bright light, whereas the bright orange one at the side means a highly reflective surface in shadow.
… [from another illusion]
So why do they look so different? Because your brain takes the image on the retina and creates what it sees according to what the information would have meant in the brain’s past experience of interacting with the world.
In this case the angles suggest depth and perspective and the brain believes the green table is longer than it is while the red table appears squarer.
The beautiful thing about illusions is they make us realise things are never what they seem, and that our experiences of the world shape our understanding of it.
Studying illusions can teach us several things. We can learn that it is easy for our senses to be fooled. We can learn about how the brain works. We can also learn how to take into account how our brain works to try and adjust our opinions (to be careful we are not just interpreting things incorrectly). It is amazing to see some of the wild guidance our brains give us. Normally they do a fantastic job of guiding us through our day but they have weaknesses that can lead us to mistaken conclusions.
Adam Wilson posted a status update on the social networking Web site Twitter — just by thinking about it. A UW-Madison biomedical engineering doctoral student, Wilson is among a growing group of researchers worldwide who aim to perfect a communication system for users whose bodies do not work, but whose brains function normally. Among those are people who have amyotrophic lateral sclerosis (ALS), brain-stem stroke or high spinal cord injury.
The interface consists, essentially, of a keyboard displayed on a computer screen. “The way this works is that all the letters come up, and each one of them flashes individually,” says Williams. “And what your brain does is, if you’re looking at the ‘R’ on the screen and all the other letters are flashing, nothing happens. But when the ‘R’ flashes, your brain says, ‘Hey, wait a minute. Something’s different about what I was just paying attention to.’ And you see a momentary change in brain activity.”
The system still is not very quick. However, as with texting, users improve as they practice using the interface. “I’ve seen people do up to eight characters per minute,” says Wilson.
This image looks like Albert Einstein up close. If you back up maybe 3-5 meters it will look like Marylin Monroe. Image by Dr. Aude Oliva.
Hybrid images paper by Aude Oliva, MIT; Antonio Torralba, MIT; and Philippe G. Schyns University of Glasgow.
We present hybrid images, a technique that produces static images with two interpretations, which change as a function of viewing distance. Hybrid images are based on the multiscale processing of images by the human visual system and are motivated by masking studies in visual perception. These images can be used to create
compelling displays in which the image appears to change as the viewing distance changes. We show that by taking into account perceptual grouping mechanisms it is possible to build compelling hybrid images with stable percepts at each distance.
Hybrid images, however, contain two coherent global image interpretations, one of which is of the low spatial frequencies, the other of high spatial frequencies.
For a given distance of viewing, or a given temporal frequency a particular band of spatial frequency dominates visual processing. Visual analysis of the hybrid image still unfolds from global to local perception, but within the selected frequency band, for a given viewing distance, the observer will perceive the global structure of the hybrid first, and take an additional hundred milliseconds to organize the local information into a coherent percept (organization of blobs if the image is viewed at a far distance, or organization of edges for close viewing).
Very cool stuff.
This is just a smaller image of the above (all I did was shrink the size). For me, this already looks like Marilyn Monroe, but also needs a shorter distance to see the image seem to change.
Life for Warwick’s robot began when his team at the University of Reading spread rat neurons onto an array of electrodes. After about 20 minutes, the neurons began to form connections with one another. “It’s an innate response of the neurons,” says Warwick, “they try to link up and start communicating.”
For the next week the team fed the developing brain a liquid containing nutrients and minerals. And once the neurons established a network sufficiently capable of responding to electrical inputs from the electrode array, they connected the newly formed brain to a simple robot body consisting of two wheels and a sonar sensor.
At first, the young robot spent a lot of time crashing into things. But after a few weeks of practice, its performance began to improve as the connections between the active neurons in its brain strengthened. “This is a specific type of learning, called Hebbian learning,” says Warwick, “where, by doing something habitually, you get better at doing it.”
“It’s fun just looking at it as a robot life form, but I think it may also contribute to a better understanding of how our brain works,” he says. Studying the ways in which his robot learns and stores memories in its brain may provide new insights into neurological disorders like Alzheimer’s disease.
There is a nasty rumor making its way around the interconnected series of tubes we call the Internet.
As visible light enters the eye and strikes the cone cells, the cells send electrical signals along the optic nerve to the brain. This is how our body “senses” light. Our brain interprets those three separate sensations to produce the perception that we call “color.”
The truth is, no color actually exists outside of our brain’s perception of it. Everything we call a color—and there are a lot more than what comes in your box of Crayolas—only exists in our heads. We define color in terms of how our brains process the stimuli produced by a mix of wavelengths in the range of 400–700nm hitting specialized cells in our eyes—”one, or any mixture, of the constituents into which light can be separated in a spectrum or rainbow,” says the OED. Elliot’s article might be better titled, “Magenta is not a single wavelength of electromagnetic radiation in the ‘visible’ spectrum, but our brain perceives it anyway.”
This is a great article that uses science to explain interesting details about our brains and how we perceive the external world.
When neurons – brain nerve cells – are grown in culture, they don’t form complex ‘thinking’ networks. Moses, Feinerman and Rotem wondered whether the physical structure of the nerve network could be designed to be more brain-like. To simplify things, they grew a model nerve network in one dimension only – by getting the neurons to grow along a groove etched in a glass plate. The scientists found they could stimulate these nerve cells using a magnetic field (as opposed to other systems of lab-grown neurons that only react to electricity).
Experimenting further with the linear set-up, the group found that varying the width of the neuron stripe affected how well it would send signals. Nerve cells in the brain are connected to great numbers of other cells through their axons (long, thin extensions), and they must receive a minimum number of incoming signals before they fire one off in response. The researchers identified a threshold thickness, one that allowed the development of around 100 axons. Below this number, the chance of a response was iffy, while just a few over this number greatly raised the chance a signal would be passed on.
The scientists then took two thin stripes of around 100 axons each and created a logic gate similar to one in an electronic computer. Both of these ‘wires’ were connected to a small number of nerve cells. When the cells received a signal along just one of the ‘wires,’ the outcome was uncertain; but a signal sent along both ‘wires’ simultaneously was assured of a response. This type of structure is known as an AND gate. The next structure the team created was slightly more complex: Triangles fashioned from the neuron stripes were lined up in a row, point to rib, in a way that forced the axons to develop and send signals in one direction only. Several of these segmented shapes were then attached together in a loop to create a closed circuit. The regular relay of nerve signals around the circuit turned it into a sort of biological clock or pacemaker.
Moses: ‘We have been able to enforce simplicity on an inherently complicated system. Now we can ask, ‘What do nerve cells grown in culture require in order to be able to carry out complex calculations?’ As we find answers, we get closer to understanding the conditions needed for creating a synthetic, many-neuron ‘thinking’ apparatus.’
It takes years for children to master the ins and outs of arithmetic. New research indicates that this learning process triggers a large-scale reorganization of brain processes involved in understanding written symbols for various quantities.
The findings support the idea that humans’ ability to match specific quantities with number symbols, a skill required for doing arithmetic, builds on a brain system that is used for estimating approximate quantities. That brain system is seen in many nonhuman animals.
When performing operations with Arabic numerals, young adults, but not school-age children, show pronounced activity in a piece of brain tissue called the left superior temporal gyrus, says Daniel Ansari of the University of Western Ontario in London, Canada. Earlier studies have linked this region to the ability to associate speech sounds with written letters, and musical sounds with written notes. The left superior temporal gyrus is located near the brain’s midpoint, not far from areas linked to speech production and understanding.
In contrast, children solving a numerical task display heightened activity in a frontal-brain area that, in adults, primarily serves other functions.