neurodudes

Expression data is now available for over 60K gene probes over the entire human brain. Click here to access this monster data set!

More info after the jump.

(more…)

A set of two articles recently came out in Science that directly visualize two different (and likely complementary) approaches to synapse specific delivery of gene products. Plasticity at specific synapses (input specificity — we’re restricting the discussion to the dendrites of the post-synaptic neuron) requires proteins (eg. new AMPA receptors) to get to those post-synaptic compartments and membranes. But the intructions for these new proteins are contained in the nucleus with the rest of the genome. Clearly, new proteins synthesized in the soma can’t just be sent everywhere, since only specific inputs (eg. particular dendritic spines) need these new proteins. How does this happen? Hence, the postulated synaptic tag.

Two approaches

Broadly, there are two approaches to synaptic tagging: 1) mRNA is distributed widely and translated locally at tagged locations; 2) protein products are distributed widely in the bodies of dendrites but only contact/off-load at tagged synaptic specializations. This News & Views gives a nice overview of the two papers, which find approach 1) in Aplysia cultures with sensorin mRNA and approach 2) in rat hippocampal neurons with Vesl-1S/Homer-1a protein. It amazes me that both were found pretty much simultaneously, but that might have more to do with the use of the photoconvertible Dendra2 protein than anything else.

With both approaches, we still don’t know why mRNA/protein is directed to a certain location. That is, we can visualize synaptic tagging but we don’t know what is the tag, its ontogeny, or the mechanism of tagging. But that might not be so important to understanding more about neural function. These new tools might allow us to image plasticity at many synapses at once, perhaps even in vivo. But before that, more work is needed… does the optical signal (from the Dendra fusion protein) correlate with degree of potentiation? Can we detect plasticity in the opposite direction, ie. synaptic depression, through another tag?  (As a sidenote to approach 1), the use of 5′ and 3′ UTRs as a sort of molecular zipcode is also intriguing.)

Cryonics never really delivered. But can we now develop the technology to preserve neural structures? Ken Hayworth thinks we can and advocates a brain preservation technology prize. It’s nice to see such big ideas.

PNAS has some interesting articles that I came across today:

1. 3D PALM (open access): Using 2-photon and photoactivatable proteins, the authors image beyond the usual sub-wavelength TIRF limits. They image over multiple microns with 50nm resolution.
2. Neuroeconomics:  Low digit ratio (2d:4d) predicts financial success in traders. Okay, measure the length of your index and ring fingers. (Not sure if this analysis applies for the ladies; the authors only used men in the study.) Calculate the ratio (2d/4d); longer ring fingers signify greater fetal androgen exposure. The mean value is about 0.96. As the authors say,
   

   Digit ratios have been found to predict performance in competitive sports, such as soccer, rugby, basketball, and skiing, so 2D:4D may also predict the risk preferences and physical speed required for high-frequency trading.

   A strong correlation (r~0.5) was found between low digit ratios and profits in short-term trading. So, they take on more risk and make more money. What I want to know is how well the low 2d:4d ratio traders did over the last 6 months!

Nature is reporting on potential flaw in multiple imaging (fMRI) studies of social neuroscience. Ed Vul (a graduate student in my dept) and colleagues have a paper in press that says that many of the high correlations between brain regions and social behavior are implausible, given the inherent variability/noise in fMRI. Furthermore, based on a survey of methods from individual investigators, they created a list of papers that commit, in their view, a statistical mistake (non-independence). Naturally, the authors named in the paper aren’t happy and, according to the Nature article, several rebuttals are in the works. At the very least, to my non-expert eyes, this seems like an important discussion to have about data analysis and methodology.

The Circadian Clock in the Retina Controls Rod-Cone Coupling (Christophe Ribelayga, Yu Cao, and Stuart C. Mangel)

An amazing paper from Neuron demonstrating adaptive (circadian clock-governed) binning in the retina, based on dopamine modulation of gap junction (electrical) synapses between retinal photodetectors. During the day, abundant dopamine release weakens gap junctions coupling rods and cones together so that visual acuity is high. When light is scarce (at night), there is less dopamine and the electrical coupling between rods and cones is increased. This is analogous to on-chip binning in CCD (digital) cameras. Binning increases signal (in light-limited systems, eg. seeing at night) by increasing optical input area and by reducing single element noise (ie. noise at different photoreceptors should be independent) at the cost of resolution. So, the retina activates photoreceptor binning at night to boost low-light signals and deactivates it during the day to increase resolution. The dopamine comes from cells in the interplexiform layer, whose dopamine release is itself governed by melatonin projections.

Also, I never knew that gap junction strengths were directly modifiable. It looks like the D2 receptors are G-protein coupled to PKA, which acts on the gap junctions.

Plants Found to Show Preferences for Their Relatives – NYTimes.com

Two amazing things here:

1. Plants missing photosynthetic enzymes of their own that migrate directionally toward “victim” plants. This behavior has an uncanny resemblance to axon guidance. Make sure to view the time-lapse video in the NYT article. Here’s an image from the PSU website:
   
   
2. Plants capable of identifying kin and “being nice” to kin while going into a competitive mode of root growth with non-kin. Amazing.

It refreshing to see this kind of interesting behavior without any neurons involved. It makes me think (realize) that the idea of a neuron or a neural system has many components and there might not be any good reason to assume that a single cell must have all of those properties or none of them. Something like a neuron-like cell that’s not a neuron in the classical sense. Anyone know of other examples?

Saw this on the Confocal list… Several times in the last few years I and others in the lab have debated the advantages and disadvantages of different fluorescence microscopy techniques. As many of you know, fluorescence microscopy is becoming increasingly important for many cool neuroscience techniques. But equally important in knowing how to properly image fluorescence.

Here’s a really thorough 2007 article from J. Microscopy that does a nice job of comparing wide-field/deconvolution, spinning disk confocal, and laser scanning confocal microscopy. Punchline is after the jump. (more…)

This new technique from Cori Bargmann’s lab is one of the neatest that I’ve seen in a while. The authors split GFP into two pieces, expressing one piece presynaptically and the other postsynaptically. This creates functional (ie. fluorescing) GFP only at sites of synaptic contact where the protein can reconstitute. They call the technique GFP Reconstitution Across Synaptic Partners (GRASP). Check out an example labeling here:

The neurons are expressing mCherry in the cytoplasm but GFP is expressed only at the site of synaptic contacts where the split GFP peptides can be reconstituted into a complete GFP fluorophore.

Video-Rate Far-Field Optical Nanoscopy Dissects Synaptic Vesicle Movement

Just the optical engineering alone here deserves mention: 28 frames per second at 62nm resolution (well below the diffraction limit of 260nm for light of the wavelength used)! STED (or stimulated emission depletion, developed in Stefan Hell’s group) is ideal for visualizing synaptic vesicles, whose small size (~50nm) has typically confined them to the domain of electron microscopists. The ability to get high-speed STED allowed the researchers to track individual vesicles and their path dynamics. They conclude that vesicle movement has both motor-driven and diffusive components (ie. a biased random walk). I’m sure with more time and more analysis there will be a lot of interesting applications for this kind of real-time vesicle tracking. Perhaps in the near future we will have single vesicle “minis” monitored at multiple sites through microscopy instead of just one or two sites electrophysiologically…

Here’s the resolution difference between STED and confocal for a single vesicle:

And, for those of you with ~$1.25M lying around, you can now purchase a STED setup directly from Leica!