Three Cheers for GCaMP : Optogenetic Brain Reading

Three papers are out online in Nature Methods that show big improvements in calcium imaging with genetically encoded sensors.  They are are based on the fluorescence intensity indicator, GCaMP.   GCaMP, first developed by Junichi Nakai, consists of a GFP that has been circularly permuted so that the N and C termini are fused and new termini are made in the middle of the protein.  Fused to one terminus is calmodulin and the other is a peptide, M13, that calmodulin (CaM) binds to in the presence of calcium. The name is supposed to look like GFP with a CaM inserted into it, G-CaM-P.  Normally the GFP is dim, as there is a hole from the outside of its barrel into the chromophore.  Upon binding calcium, this hole is plugged and fluorescence increases.

The first paper, A genetically encoded reporter of synaptic activity in vivo, from Leon Lagnado’s group, targets GCaMP2 to the outer surface of synaptic vesicles. This localization allows the fluorescence signal to be confined to the presynaptic terminal, where calcium fluxes in response to action potentials are high.  This targeting improves the response magnitude of GCaMP2 and permits the optical recording of synaptic inputs into whatever region of the brain one looks at.  They demonstrate the technique in live zebrafish.

In the second paper, Optical interrogation of neural circuits in Caenorhabditis elegans, from Sharad Ramanathan’s group, GCaMP2 has been combined with Channelrhodopsin-2 to perform functional circuit mapping in the worm.   Since the worm’s structural wiring diagram has been essentially solved, functional data could say much about how “thick” the wires between each cell are.  Unfortunately, with GCaMP2, the responses are too slow and weak to distinguish direct from indirect connections.

Finally, we have published a paper, Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators, describing the improved GCaMP3.  This indicator has between 2-10x better signal to noise than GCaMP2, D3cpv and TN-XXL, depending on the system you are using.  It’s kinetics are faster and it is more photostable than FRET indicators, and the responses are huge.  When expressed in motor cortex of the mouse, neuronal activity is easily seen directly in the raw data.  Furthermore, the sensor can be expressed stably for months, making it a potential tool for observing how learning reshapes the patterns of activity in the cortex.

Imaging of mouse motor cortex (M1) expressing the genetically-encoded calcium indicator GCaMP3 through a cortical window. After 72 days of GCaMP3 expression, large fluorescence transients can be seen in many neurons that are highly correlated with mouse running.

GCaMP3 is not perfect. It cannot reliably detect single action potential in vivo in mammals, though I doubt that any existing GECI can. Work continues on future generations of GCaMP that may achieve 100% fidelity in optical reading of the bits in the brain. However, there is considerable evidence from a number of groups that have been beta-testing the sensor, including the Tank lab of “quake mouse” fame, that it is a significant leap forward and unlocks much of the fantastic and fantasized potential of genetically-encoded calcium indicators.

Comparison of fluorescence changes in response to trains of action potentials in acute cortical slices.

I will try to post a more complete writeup of GCaMP3 for Brain Windows soon, with an unbiased eye to its strengths and weaknesses.  We worked very hard to carefully characterize this sensor’s effects on cellular and circuit properties.  If you have any questions about GCaMP3, please post them to the comments.

For further info about strategies for GECI use and optimization, check out our previous paper, Reporting neural activity with genetically encoded calcium indicators in Brain Cell Biology.

The official press release from HHMI regarding GCaMP3 is available here.

Annual Reviews worth reading

Annual Reviews of Neuroscience published their 2009 issue recently.  These articles are usually a great way to catch up with a field, particularly when they are recently published.  Here are a few that might be of interest to the Brain Windows reader.

Synaptic Mechanisms for Plasticity in Neocortex

Daniel E. Feldman

Sensory experience and learning alter sensory representations in cerebral cortex. The synaptic mechanisms underlying sensory cortical plasticity have long been sought. Recent work indicates that long-term cortical plasticity is a complex, multicomponent process involving multiple synaptic and cellular mechanisms. Sensory use, disuse, and training drive long-term potentiation and depression (LTP and LTD), homeostatic synaptic plasticity and plasticity of intrinsic excitability, and structural changes including formation, removal, and morphological remodeling of cortical synapses and dendritic spines. Both excitatory and inhibitory circuits are strongly regulated by experience. This review summarizes these findings and proposes that these mechanisms map onto specific functional components of plasticity, which occur in common across the primary somatosensory, visual, and auditory cortices.

Using Diffusion Imaging to Study Human Connectional Anatomy

Heidi Johansen-Berg and Matthew F.S. Rushworth

Diffusion imaging can be used to estimate the routes taken by fiber pathways connecting different regions of the living brain. This approach has already supplied novel insights into in vivo human brain anatomy. For example, by detecting where connection patterns change, one can define anatomical borders between cortical regions or subcortical nuclei in the living human brain for the first time. Because diffusion tractography is a relatively new technique, however, it is important to assess its validity critically. We discuss the degree to which diffusion tractography meets the requirements of a technique to assess structural connectivity and how its results compare to those from the gold-standard tract tracing methods in nonhuman animals. We conclude that although tractography offers novel opportunities it also raises significant challenges to be addressed by further validation studies to define precisely the limitations and scope of this exciting new technique.

The Science of Neural Interface Systems

Nicholas G. Hatsopoulos and John P. Donoghue

The ultimate goal of neural interface research is to create links between the nervous system and the outside world either by stimulating or by recording from neural tissue to treat or assist people with sensory, motor, or other disabilities of neural function. Although electrical stimulation systems have already reached widespread clinical application, neural interfaces that record neural signals to decipher movement intentions are only now beginning to develop into clinically viable systems to help paralyzed people. We begin by reviewing state-of-the-art research and early-stage clinical recording systems and focus on systems that record single-unit action potentials. We then address the potential for neural interface research to enhance basic scientific understanding of brain function by offering unique insights in neural coding and representation, plasticity, brain-behavior relations, and the neurobiology of disease. Finally, we discuss technical and scientific challenges faced by these systems before they are widely adopted by severely motor-disabled patients.

Advances in Light Microscopy for Neuroscience

Brian A. Wilt, Laurie D. Burns, Eric Tatt Wei Ho, Kunal K. Ghosh, Eran A. Mukamel, and Mark J. Schnitzer

Since the work of Golgi and Cajal, light microscopy has remained a key tool for neuroscientists to observe cellular properties. Ongoing advances have enabled new experimental capabilities using light to inspect the nervous system across multiple spatial scales, including ultrastructural scales finer than the optical diffraction limit. Other progress permits functional imaging at faster speeds, at greater depths in brain tissue, and over larger tissue volumes than previously possible. Portable, miniaturized fluorescence microscopes now allow brain imaging in freely behaving mice. Complementary progress on animal preparations has enabled imaging in head-restrained behaving animals, as well as time-lapse microscopy studies in the brains of live subjects. Mouse genetic approaches permit mosaic and inducible fluorescence-labeling strategies, whereas intrinsic contrast mechanisms allow in vivo imaging of animals and humans without use of exogenous markers. This review surveys such advances and highlights emerging capabilities of particular interest to neuroscientists.

High-resolution deep-brain two-photon imaging

Mark Schnitzer, who recently became an HHMI Investigtor, has a new paper out on improved optics for his group’s miniature probe microscopes.  Mark has been pioneering these tiny probes to do optical imaging in deep brain structures, and is one of the only games in town if you want to look deeper then a millimeter into the brain without sucking off all the ‘irrelevant mush’ in between your microscope and the part of the brain you are interested in.  A beer-lubricated former Bell Labs employee (not Karel) years ago confided to me that he wasn’t too impressed with these microprobe systems,because “its just a GRIN lens on a stick”, ignoring the painstaking engineering and minaturization of motor, supports and light paths.  The limitations were quite significant though, in this new Nature Methods communication, In vivo fluorescence imaging with high-resolution microlenses, Barretto et al. note that “The best Rayleigh resolutions values achieved by two-photon fluorescence imaging with GRIN lenses are ~1.6 um lateral and ~12um axial, yielding highly elongated point spread functions that impede acquisions of high-quality, three-dimensional image stacks.”  That elongated point spread function really blurs the image and dramatically reduces the power and brightness of the two-photon imaging mode.  I assume this is why most of the data I’ve seen Mark present was with one-photon illumination.  Now, the authors have addressed this shortcoming.

 

Design of the lens system. The resolution is comparable to a standard 40x microscope objective.

 

 

      They coupled a plano-convex lens to a custom fabricated GRIN lens whose refractive properties were designed to compensate for the spherical aberration of the plano-convex lens. This system achieved near diffraction-limited resolution in both the lateral and axial dimensions.  Rather then the dim blur of previous iterations, the new system clearly resolves synaptic spines on the dendrites of fluorescent neurons buried deeply in the hippocampus of live mice. The example system in the paper has a 1mm diameter, while the previous systems were as narrow as 0.3mm, so there is still plenty of room for further miniaturization, although I’m not sure how that would affect the light gathering capacity of the lens. Importantly, Mark’s systems are finally getting commercialized so that a much larger scientific population can start to benefit from the technology soon. 

 

A hippocampal neuron (e) in a live mouse visualized with the new system (c) vs. the old system (d)

Journal Scan – Transynaptic tracing, fly olfaction, fast super-resolution, localization of perception

Here’s a group of four recent papers that are worth checking out but I don’t have the time to cover.  The first provides a set of tools for neuronal circuit tracing. The second pushes super-resolution imaging into fast, live-cell imaging.  The third, by a friend from graduate school, uses G-CaMP to make strong claims about olfactory coding in fruit flies. The last reports remarkable data pointing to the distributed nature of conscious perception in humans, which would have been a great data set to reference in my recent talk on free will.

Genetically timed, activity-sensor and rainbow transsynaptic viral tools 

We developed retrograde, transsynaptic pseudorabies viruses (PRVs) with genetically encoded activity sensors that optically report the activity of connected neurons among spatially intermingled neurons in the brain. Next we engineered PRVs to express two differentially colored fluorescent proteins in a time-shifted manner to define a time period early after infection to investigate neural activity. Finally we used multiple-colored PRVs to differentiate and dissect the complex architecture of brain regions.

Super-resolution video microscopy of live cells by structured illumination

Structured-illumination microscopy can double the resolution of the widefield fluorescence microscope but has previously been too slow for dynamic live imaging. Here we demonstrate a high-speed structured-illumination microscope that is capable of 100-nm resolution at frame rates up to 11 Hz for several hundred time points. We demonstrate the microscope by video imaging of tubulin and kinesin dynamics in living Drosophila melanogaster S2 cells in the total internal reflection mode.

Select Drosophila glomeruli mediate innate olfactory attraction and aversion.

Fruitflies show robust attraction to food odours, which usually excite several glomeruli. To understand how the representation of such odours leads to behaviour, we used genetic tools to dissect the contribution of each activated glomerulus. Apple cider vinegar triggers robust innate attraction at a relatively low concentration, which activates six glomeruli. By silencing individual glomeruli, here we show that the absence of activity in two glomeruli, DM1 and VA2, markedly reduces attraction. Conversely, when each of these two glomeruli was selectively activated, flies showed as robust an attraction to vinegar as wild-type flies. Notably, a higher concentration of vinegar excites an additional glomerulus and is less attractive to flies. We show that activation of the extra glomerulus is necessary and sufficient to mediate the behavioural switch. Together, these results indicate that individual glomeruli, rather than the entire pattern of active glomeruli, mediate innate behavioural output.

Movement Intention After Parietal Cortex Stimulation in Humans

Parietal and premotor cortex regions are serious contenders for bringing motor intentions and motor responses into awareness. We used electrical stimulation in seven patients undergoing awake brain surgery. Stimulating the right inferior parietal regions triggered a strong intention and desire to move the contralateral hand, arm, or foot, whereas stimulating the left inferior parietal region provoked the intention to move the lips and to talk. When stimulation intensity was increased in parietal areas, participants believed they had really performed these movements, although no electromyographic activity was detected. Stimulation of the premotor region triggered overt mouth and contralateral limb movements. Yet, patients firmly denied that they had moved. Conscious intention and motor awareness thus arise from increased parietal activity before movement execution.

Symposium : A Revolution in Fluorescence Imaging

This coming Tuesday and Wednesday (Feb 17th & 18th) at UCSD, there will be a symposium honoring Roger Tsien, featuring presentations from 32 former and current members of the Tsien Lab. The topics are quite diverse, concentrated in genetically-encoded indicators, but also featuring fluorescent cell penetrating peptides for cancer therapy, photophore ligases for imaging synaptic development, and even a radical new design for the internal combustion engine.

The quality of speakers and subjects looks to be outstanding.  Here is a complete schedule.  You may notice that at 11:15 AM on Tuesday in Price Center East Ballroom, I will be presenting recent progress we have made in the development of genetically-encoded calcium indicators and their application to in vivo imaging.  Don’t miss that one!  :)  Roger’s talk, which will assuredly be equal parts absorbing, humorous, and illuminating, is at 4pm Wednesday in the Price Center Theater.

If you live in Southern California and are interesting in imaging technology, there isn’t a better place to be than this symposium.  If you can’t make it, Brain Windows will have a full write-up following the event.

Here is the un-official schedule.

Tuesday February 17th – Price Center East Ballroom

9:00 -9:05 Varda  Levram -Ellisman Opening

9:05-9:15 Palmer Taylor

Designing the next generation of genetically encoded sensors

9:15-9:30 Roger Heim

FRET for compound screening at Aurora/Vertex

9:30-9:45 Amy Palmer

Designing and using genetically encoded sensors: Lessons I learned from Roger

9:45-10:00 Robert Campbell

Beyond brightness: colony screens for fluorescent protein photo stability and biosensor FRET changes

10:00-10:15 Colette Dooley

GFP sensors for reactive oxygen species: Tying up loose ends and looking forward.

10:15-10:30 Peter Wang

Fluorescent Proteins and FRET biosensors for visualizing cell motility and mechanotransduction

Fluorescent proteins in neuroscience

11:00-11:15 Brian Bacskai

Aberrant calcium homeostasis in the Alzheimer mouse brain

11:15-11:30 Andrew Hires

Watching a mouse think: Novel fluorescent genetically-encoded calcium indicators applied to in vivo brain imaging

11:30-11:45 Alice Ting

Imaging synapse development with engineered photophore ligases

11:45-12:00 Rex Kerr

3D calcium imaging in C. elegans

Clinical applications

12:00-12:15 Todd Aguilera

Activatable Cell Penetrating Peptides for use in clinical contrast agent and therapeutic development

12:15-12:30 Quyen Nguyen

Surgery with Molecular Fluorescence Imaging Guidance

Fluorescent probes (Chemistry)

1:30-1:45 Tito Gonzalez

Voltage-Sensitive FRET Probes & Applications

1:45-2:00 Paul Negulescu

From watching ions to moving them

2:00-2:15 Timothy Dore

Roger-Inspired Photochemistry: Releasing Biological Effectors with 2PE

2:00-2:15 Joe Kao

Electron Paramagnetic Resonance Imaging in Living Animals

2:15-2:30 Brent Martin

Chemical probes for studying protein acylation

2:30-2:45 Jianghong Rao

Non-GFP based probes for imaging of the hydrolytic enzyme activity

Cellular research with and without Fluorescent probes

3:15-3:30 Carsten Schultz

Cell membrane repair visualized by GFP fusion proteins

3:30-3:45 David Green

Transcriptomes and Systems Biology: application to early mammalian embryogenesis

3:45-4:00 Clotilde Randriamampita

Paradoxical aspects of T cell activation revealed with fluorescent proteins

4:15-4:30 Wen-Hong Li

Studying dynamic cell-cell communication in vivo by Trojan-LAMP

4:30-4:45 Martin Poenie

Aim and Shoot: Two roles for dynein in T cell effector function

4:45-5:00 Gregor Zlokarnik

From bla to blah, blah in 20 years

5:00-5:15                        James Sharp

President, Zeiss MicroImaging Gmbh

February 18 2009 – Leichtag 107

Cellular research with and without fluorescent proteins

9:00-9:15 David Zacharias

Fluorescent Proteins, Palmitoylation and Cancer: two out of three ain’t bad

9:15-9:30 Jin Zhang

Visualization of Cell Signaling Dynamics: A Tale of MAPK

9:30-9:45 Paul Sammak

Nuclear organization and movement in pluripotent stem cells measured by Histone GFP H2B

Branching out

9:45-10:00 Yong Yao

NIH Toolbox Program

10:00-10:15 Oded Tour

The Tour Engine – A novel Internal Combustion Engine with the potential to boost efficiency and cut emissions

Into the future

10:45-11:00 Xiaokun Shu

Visibly and infrared fluorescent proteins: photophysics and engineering

11:00-11:15 Michael Lin

Engineering fluorescent proteins for visualizing newly synthesized proteins and improving FRET-based biosensors

11:15-11:30 Jeremy Babendure

Training our next generation of Fluorescent Protein Enthusiasts

Main Event – Price Center Theater

4:00-5:00 Roger Tsien

Chancellor invitational lecture 2008 Nobel Prize in Chemistry

BrainStorm 1 : The Calcium Memory Sensor

As mentioned in the previous post, this is the first installment of BrainStorm, a section of ideas I have under development, but don’t have the time to physically work on.  This section will contain organically developed ideas, organized by project.  Reader feedback is encouraged.

How can we identify the group of neurons that encode a particular thought?  

I don’t want to simply see correlations of in activity of a few scattered neurons with a given thought, but identify the entire neuronal ensemble.  Which neurons are active at a precise moment in a task?  How are they wired together? Which are the drivers of activity?

Existing technology is inadequate to identify the entire neural ensemble that encodes a thought. Immediate early gene expression  patterns have not been shown to be precisely correlated with brain activity, and have a temporal resolution on the order of minutes. Genetically encoded calcium sensors (GECIs) have the necessary temporal and spatial resolution, but their response is nearly as fleeting as a thought, making it impossible to simultaneously record from networks of thousands of possible participants with current microscopy techniques.

In BrainStorm 1, I will outline a technology, photoswitchable genetically-encoded calcium memory sensors, that can identify all the neurons in a large network that are active during user-specified, aribitrarly brief or long time periods.  I will propose four potential strategies for construction of these sensors, and detail practical considerations for sensor design, screening and application.

The Journal of Visualized Experiments

For technically demanding protocols in neuroscience (or any other science) research, a printed protocol is often insufficient to capture all the essentials of a method.  There are usually numerous ‘tricks’ or things that one must pay attention to that are not included in the printed page.  Or, if they are included, they still lack a vivid description. Many techniques require the novice to be taught the technique from a more experienced colleage. Unfortunately, it is not always easy to find someone skilled to be trained from.  Labs which pioneer the techniques have only a limited amount of time and resources available to train outside scientists. How can advanced scientific skills be distributed more broadly and efficiently? A good place to start is the Journal of Visualized Experiments (JoVE). It’s a YouTube for science protocols.

So that's how you do it!

JoVE is a growing collection of video protocols that walk a researcher through the procedure, allowing one to actually see the steps used, rather than just imaging what performing the protocol might be like. Want to know how to glue a live fruit fly to a stick?  Just watch the video! Wonder how to load calcium dyes onto the cortex of a mouse? Just watch the video!  This looks to be a fantastic resource for people that are learning a technique, that want to see other possible ways to do a procedure, or those who are simply curious about what a neuroscientist actually does at work.

I should make one for glutamate imaging!

Updated: fMRI Based Visual Stimulus Reconstruction

A simple view of what the brain does is acquire input, process it, then produce output. One strategy for understanding what processing takes place is to record the patterns of brain activity while showing many patterns of input, then see if you can use the information gained to predict a novel input, given the pattern of brain activity. The canonical example of this approach is visual input reconstruction based on recorded spike trains in the visual system of the blowfly.

The blowfly is a relatively simple system (though quite efficient) with a tiny brain. Could a similar approach work in humans?  Although we can’t drop electrodes into the visual cortex (usually), we can put people in fMRI scanners to visualize the pattern of blood oxygenation, which is correlated with neural activity.

In Visual Image Reconstruction from Human Brain Activity using a Combination of Multiscale Local Image Decoders, Miyawaki et al demonstrate visual input prediction using fMRI responses. Using 3mm³ voxels, the group measured the activity level across early visual cortex (V1-V4) for numerous 10×10 binary patterns of visual stimuli. They looked at correlations in 1×1, 1×2, 2×1 and 2×2 bins of voxel activity to hundreds of visual test patterns. The activity represented local image elements. Then they displayed novel visual input and used a linear combination of the local image element responses to predict the visual input from the brain activity alone. It is noteworthy that they only required several hundred training images before visual input prediction was possible.

Predicted visual input from fMRI activity in V1 and V2

Note that a rentinotopic map, where the relative spatial position of visual input is reflected in the activity across the visual cortex, is not strictly required for this technique to work. What is required is that the response of each local element is consistent across similar patterns of input in the element’s receptive field. Furthermore, the spatial scale of pattern representation in early processing regions of human visual cortex is broad enough to be picked up by the fMRI scanner.

It would be interesting to see how much higher visual resolution could be predicted with an fMRI approach. Could this approach be adapted to predict input from the responses of cells with more complex receptive fields in higher cortical areas? Or, are those cells too intermingled with neighbors with vastly different response properties to be separable by fMRI?  Higher areas are vital for our own brains to rapidly perceive the contours of complex images. I’d also like to see how well non-contiguous images are predicted.

Cellular resolution calcium imaging with bulk loaded dyes has been used to map fine-grained detail of receptive fields in lower animals visual and somatosensory cortex. Is input prediction possible from these recordings? Is the input training set too limited? Could more complex input be perceived using a fewer number of complex cells from higher visual areas (V2 and above)?

Preview : fMRI Based Visual Stimulus Reconstruction

I’m going to try a new format for getting brand-new articles up on the site quickly. Often, I want to post something but don’t have the time to read the paper carefully and then create a quality writeup. This provides a lot of posting inhibition. Rather than just sit on the paper, I’ll now post the paper, the link, and the abstract.  Then, if and when I find the time, I’ll post and update and go more in depth.  Here’s the first preview!

Please see the updated post on this paper.

Visual Image Reconstruction from Human Brain Activity using a Combination of Multiscale Local Image Decoders

Yoichi Miyawaki^1,2,6,Hajime Uchida^2,3,6,Okito Yamashita²,Masa-aki Sato²,Yusuke Morito^4,5,Hiroki C. Tanabe^4,5,Norihiro Sadato^4,5andYukiyasu Kamitani^2,3,,

Perceptual experience consists of an enormous number of possible states. Previous fMRI studies have predicted a perceptual state by classifying brain activity into prespecified categories. Constraint-free visual image reconstruction is more challenging, as it is impractical to specify brain activity for all possible images. In this study, we reconstructed visual images by combining local image bases of multiple scales, whose contrasts were independently decoded from fMRI activity by automatically selecting relevant voxels and exploiting their correlated patterns. Binary-contrast, 10 10-patch images (2¹⁰⁰ possible states) were accurately reconstructed without any image prior on a single trial or volume basis by measuring brain activity only for several hundred random images. Reconstruction was also used to identify the presented image among millions of candidates. The results suggest that our approach provides an effective means to read out complex perceptual states from brain activity while discovering information representation in multivoxel patterns.