Humans imitate humans more than chimps do

This nytimes article describes an experiment in which

1) In front of chimps, human researchers demonstrate opening a box, but they throw in some unnecessary steps. The box is constructed so that an onlooker can figure out which steps are unnecessary just by watching. The chimps learn to open the box, but skip the unnecessary steps.
2) In front of human children, the researchers do the same thing. The children learn to open the box, but are careful to do exactly what the demonstrator did, including the unnecessary steps.

The children’s awareness of which steps were unnecessary in condition (4) is shown by having some children who do not get to see a demonstration of how to open the box. These children are able to figure out how to open it (without the unnecessary steps, of course).

Thus, human children, as compared to chimps, are more likely to imitate exactly what they see.

Victoria Horner, Andrew Whiten. Causal knowledge and imitation/emulation switching in chimpanzees (Pan troglodytes) and children (Homo sapiens), Animal Cognition, Volume 8, Issue 3, Jul 2005, Pages 164 – 181

A simulation the size of the entire human brain

From Eugene Izhikevich’s website (which by the way is full of cool stuff that we’ll probably post about someday):

“On October 27, 2005 I finished simulation of a model that has the size of the human brain. The model has 100,000,000,000 neurons (hundred billion or 10^11) and almost 1,000,000,000,000,000 (one quadrillion or 10^15) synapses. It represents 300×300 mm^2 of mammalian thalamo-cortical surface, specific, non-specific, and reticular thalamic nuclei, and spiking neurons with firing properties corresponding to those recorded in the mammalian brain. The model exhibited alpha and gamma rhythms, moving clusters of neurons in up- and down-states, and other interesting phenomena (watch a 25M .avi or .mov movie).

One second of simulation took 50 days on a beowulf cluster of 27
processors (3GHz each). Why did I do that?

Electrophysiology: Getting rid of the artists

In this nice open-access (ie. free!) essay in October’s PLoS Biology, David Kleinfeld and Oliver Griesbeck describe the revolution in neural recording that is taking electrophysiology from the realm of dark-arts (lots of training) to simpler genetically-encoded, imaging-based techniques. A lot of ground is covered in the article, including the creation of many new colors of fluorescent proteins (XFPs) that can be genetically targeted and the tagging of the XFPs with Ca, voltage, and pH sensors. A nice summary table is included comparing the techniques too:

XFP indicator tables

As you have likely noticed, Bayle and I post heavily about these new recording techniques because of our strong belief that a lot of neuroscience will be enabled by improving our ability to stimulate and record from entire networks of neurons with high resolution. Yesterday, I was listening to one of the many recent neuroscience talks here at MIT in which philosopher Pat Churchland suggested, as many others also have, that the problem of consciousness might be more of an artifact of primitive science than an actual scientific problem. She made a very nice analogy with a problem from centuries ago when scientists were unsure about the existence of life forces and what precisely made an animal alive. Of course, with modern cell biology, we now have a cellular theory of life, disease, and death. (To be fair, Churchland went on to say that people like Christof, Crick et al. are misguided in attempting to study neural correlates of consciousness. I completely disagree with that; at the very least, those scientists are helping to extend our understanding of the visual system and the difference between perception that we are aware of [conscious] and perception that has a neural correlate but that we are not aware of [unconscious]. Honestly, who cares if they say they’re studying consciousness or not — make a judgement based on the science.)