neurodudes

There’s been some work recently on looking at second harmonic generation for optical readout of action potentials… any opinions on this work?

First a brief primer on SHG (from Yuste’s recent Nature Methods paper on fluorescence microscopy):

In SHG, high-infrared light intensity drives the lowest-order nonlinear polarizability of molecules (or groups of molecules) in the specimen so that coherent light of exactly double frequency (or half the wavelength) is emitted. Because the process can occur away from resonance frequencies, there is no absorption of light, thus avoiding complications of photochemistry. This phenomenon is rare and requires, like two-photon excitation, a high concentration of photons at the focal point, something that also gives it optical sectioning. SHG is particularly interesting because it only occurs where chromophores are oriented in noncentrosymmetric arrays, such as chromophores adsorbed to biological membranes or other chemical interfaces. Thus, SHG is perhaps the only optical technique that is truly sensitive to biological membranes, something which makes it ideal for detecting changes in membrane potential. As many important biological processes, such as electrophysiological communication, detection and transduction of external molecules and cell-cell interactions occur at plasma membranes, SHG is likely to become a very useful tool for biologists.

Seed papers:

• Overcoming photodamage in second-harmonic generation microscopy: Real-time optical recording of neuronal action potentials [PNAS Open Access, Feb 2006] , L. Sacconi, D. A. Dombeck, and W. W. Webb
• Imaging membrane potential in dendritic spines [PNAS, Jan 2006] , Mutsuo Nuriya, Jiang Jiang, Boaz Nemet, Kenneth B. Eisenthal, and Rafael Yuste

A recent study in the Journal of Cognitive Neuroscience has isolated activation in the brain during a 3-stage model of deductive reasoning.

The study shows that during the ‘premise processing’ stage, there is more activity in occipito-temporal areas. During the ‘integration phase’, anterior prefrontal cortex is more active. During the final ‘valdiation phase’, the find more activity in posterior parietal and prefrontal areas.

AI started working on reasoning early on. Will studies like this lead us to the next advance in building models of reasoning?

Rein on pain lays mainly in the brain, researchers find

People looking at their own anterior cingulate are able to control their pain. Neat.

Importantly, here are the controls cited in the press release:

Researchers used multiple control groups to ensure against this: The first remained outside the MRI machine; the second received no imaging feedback; the third was shown different areas of the brain that don’t process pain; and members of the fourth group were shown someone else’s brain activity. None of the control subjects showed an ability to control pain levels.

Full PNAS article here. (free via Open Access)

When Bad People Are Punished, Men Smile (but Women Don’t) – New York Times

I think there has been studies similar to this before… here’s the relevant details:

Furthermore, researchers found that the brain’s pleasure centers lit up in males when just punishment was meted out.

The researchers cautioned that it was not clear if men and women are born with divergent responses to revenge or if their social experiences generate the responses.

A Resilient, Low-Frequency, Small-World Human Brain Functional Network with Highly Connected Association Cortical Hubs (Achard et al., 2006)

A study on network properties of the whole brain (functional connectivity data from fMRI)… interesting to see this type of work published in J. Neurosci. Building on previous fMRI/whole brain connectivity studies, the authors use a set of wavelet basis functions to estimate the correlations between different anatomical regions.

Also includes some analyses on resiliency of the system (via a metric like “largest connected cluster”) to random and targeted attack (ie. node deletion). It would be neat if they also did some analysis of common stroke damage. I would think that a stroke probably doesn’t qualify as a “targeted attack”, in the traditional sense, but, due to the predefined structure of the major circulatory structures (eg. circle of Willis), there are likely regions that are near the most commonly blocked arteries, etc. Perhaps someone with some medical qualifications could weigh in here?

There is also a nice discussion of why the human brain does not appear to be a scale-free network: That nodes do not seem to follow the “rich-get-richer” rule of preferential attachment. Evolutionarily recent structures like prefrontal seem to be among the hubs of the system and older structures like limbic regions do not dominate. Here’s a picture of the connectivity map from the paper:

Full abstract after the jump.
(more…)

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:

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.)

This Is Your Brain Under Hypnosis – New York Times

Very interesting stuff. Subjects were hypnotized and told that days later they would see “gibberish” symbols printed in particular colors. They needed to report back the color that the word appeared in. (For those unfamiliar, the Stroop test presents color words, like “red”, in a different color, such as the word “red” written with green ink. People have difficulty reporting the color of the word because we have a strong need to “read” the written word.)

The highly hypnotizable subjects (grouped according to a predetermined measure) essentially showed no Stroop effect (ie. no reaction time difference with conflicting word and color). And, with fMRI, they saw that normally activated visual-reading areas were not activated in these subjects.

New genetically encoded fluorescent voltage-sensitive dye.

Sensitivity: up to 34% change (delta F/F) per 100 mV.
Time constant: .5 ms.
Phototoxicity: You can expose the cells to light for up to 100 seconds without much effect; over 200 seconds is noticably damaging.
Location: specific to cell membranes.
Not ratiometric (if you don’t know what that is, don’t worry about it).

Excerpt from figure caption: “(c) Confocal section of HEK293 cells expressing eGFP-F shows very little fluorescence from internal membranes. Scale bar, 20 mum. (d) Fluorescence response (shown as colored increments) of hVOS on voltage pulses from -120 to +120 mV in steps of 20 mV from a holding potential of 0 mV in patch-clamped HEK293 cells.”

Baron Chanda, Rikard Blunck, Leonardo C Faria, Felix E Schweizer, Istvan Mody and Francisco Bezanilla. A hybrid approach to measuring electrical activity in genetically specified neurons. Nature Neuroscience 8, 1619 – 1626 (2005)

Can Brain Scans See Depression? – New York Times

At first glance, this doesn’t seem like anything new (imaging-wise) to neuroscientists, but there are some interesting opinions in the article.

Interesting fact:

In a range of studies, researchers have found that people with schizophrenia suffer a progressive loss of their brain cells: a 20-year-old who develops the disorder, for example, might lose 5 percent to 10 percent of overall brain volume over the next decade, studies suggest.

And I like the way this guy thinks:

In an interview, Dr. Amen said that it was unconscionable that the profession of psychiatry was not making more use of brain scans. “Here we are, giving five or six different medications to children without even looking at the organ we’re changing,” he said.

But is this true?

“The thing for people to understand is that right now, the only thing imaging can tell you is whether you have a brain tumor,” or some other neurological damage, said Paul Root Wolpe, a professor of psychiatry and sociology at the University of Pennsylvania’s Center for Bioethics.

Does anyone know of any good work applying machine learning to doing discrimination of neural disease (like ADD, general depression, and anything that’s basically not a giant lesion/tumor) in imaging scans?