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  1. Sonogenetics - A non-invasive method to manipulate neurons During the AM poster sessions, one that caught my eye was from the Chalasani Lab at the Salk Institute in La Jolla, California. Several years ago, they described a method by which they could control neural activity in the nematode worm C. elegans using focused ultrasound. This paper demonstrated that ectopic expression of the mechanosensitive channel TRP-4 in neurons rendered them sensitive to ultrasound stimulation. This is a big deal because other so called ‘non-invasive’ neural manipulation techniques like optogenetics require a fiber optic probe to be placed near the cells of interest, making the manipulation of deep brain structures with high temporal precision tedious. Sonogenetics allows for non-invasive control of neural activity. Here, in C. elegans with PVD neurons expressing the ultrasound-sensitive protein (TRP-4) and the calcium indicator GCaMP3, we can see that ultrasound exposure drastically increases calcium activity in these neurons, indicating ultrasound mediated neural activation. Warmer colors indicate more GCaMP3 fluorescence = more activity (Credit: Ibsen et al., 2015; Nature Communications) This was to be just the first step in a long process of isolating different mechanosensitive proteins and screening them in mammalian cells to find one just right for use in more complicated organisms. During the poster session this morning, Corinne Lee-Kubli, a post-doc in the Chalasani lab, provided an update on the progress in sonogenetics to date. Using an in vitro screening method to identify ultrasound-sensitive mechanoreceptors, Corinne expressed a large variety of putative channels in cells in a dish. These cells were co-transfected with the calcium indicator GCaMP6f, a powerful and fast reporter of cell activity. The fluorescent signal was then monitored before, during, and after ultrasound stimulation in a high-throughput manner. A subset of the putative mechanoreceptors were packaged into cre-dependent AAV-viral vectors and delivered to AgRP neurons deep in the brain (arcuate nucleus) of AgRP-cre mice. Validation of the excitatory actions of the ultrasound sensitive protein was done using a feeding assay, as AgRP neurons strongly promote feeding. Upon ultrasound (10 MHz) stimulation of the head (through the skull and entire brain), a few of the channels strongly promoted feeding responses, a trait not observed in mice expressing the control virus (encoding GFP). An important note is that ultrasound stimulation alone had no effect on feeding responses, indicating a specific effect of the putative mechanoreceptor in AgRP neurons. AgRP neurons in the arcuate nucleus expressing the calcium indicator GCaMP6. These cells are powerful regulators of feeding behavior and metabolism (Credit: Srisai et al., 2017; Nature Communications) This proof-of-principle application represents a significant advancement for the nascent field of sonogenetics. Much more research needs to be done to discover the most potent and specific ultrasound sensitive protein, the kinetics of said protein, and additional tools for cell inhibition. In the future, we can expect to see multiple channels expressed in different cellular populations, each sensitive to different ultrasound frequencies. Then, ‘nested’ delivery of different ultrasound waveforms could putatively activate and/or inhibit discrete cell populations across the entire brain, simultaneously or with tight temporal control. The power of this technique is impressive, as ultrasound can easily reach through the entire mouse brain at 10 MHz, and can go much deeper (e.g., in rat or primate brain) using lower frequencies. I look forward to what’s to come! Jeremy C. Borniger, PhD Department of Psychiatry & Behavioral Sciences Stanford University SoM
  2. Expansion Microscopy - ‘Just add water’ Microscopes are getting beefier and beefier, more complex and expensive, with the sole purpose of being able to see tiny, tiny things just a little bit better. Enter ‘expansion microscopy’, an idea that literally works in the opposite direction to that goal. Instead of ‘zooming in closer’, expansion microscopy aims to ‘blow things up’ in order to see the (once) tiny details (like synapses, or nuclear pores…) on a conventional microscope. Remember those dinosaurs that would expand when you added water as a kid? I sure do…and expansion microscopy works pretty much the same. Although this technology has been around for a few years, it is just getting started in terms of its ease of use, applicability to different samples (proteins, RNA, DNA, lipids…), and support community. All info on this fascinating technique is available at ExpansionMicroscopy.org. First described by Edward Boyden and colleagues at the MIT Media Lab in 2015, expansion microscopy is rapidly being applied across fields, species, and disciplines to examine extremely fine structures at the nanoscale (10-20 nm). Expansion microscopy allows for uniform expansion of a biological sample. Here, we see a brain slice (in panel B) which has been weaved into a polymer mesh with biomolecular anchors. When the polymer is expanded (‘Just add water’), it pulls the biomolecules along with it, maintaining the relative spacing between structures. In (C ) we can see that same brain slice ‘expanded’, revealing tiny pieces of biology previously too small to see (Credit: Chen et al., 2015; Science). Ed Boyden provided a ‘state of the art’ summary of expansion microscopy to date at a minisymposium today titled “new observations in neuroscience using superresolution microscopy” chaired by Michihiro Igarashi. He gave a quick overview on how they developed the idea that was to become expansion microscopy, through adapting old techniques from the early 1980’s. Next, he discussed the problems of ‘expansion’, the primary one being ’ how can we evenly expand a sample without losing valuable spacial relationships between proteins, DNA, RNA etc…? To overcome this problem they needed to develop biomolecular anchors, which link the molecular target to the polymer mesh. In this way, isometric expansion of the mesh results in the same for the anchored sample. Using this technique, many researchers have expanded tissues to look at things like synaptic proteins and microtubules at a much finer detail than what was previously possible with conventional confocal microscopes. Others have adapted the technique to work with in situ hybridization, allowing for expansion and quantification of RNA. Dr. Boyden’s lab is also working on expanding non-soft tissues, like bone, and using expansion microscopy in the clinic to diagnose and investigate cancer in unprecedented detail (so called ‘expansion pathology’). By combining expansion microscopy with RNA visualization (ExFISH) and sequencing (MERFISH), hundreds of transcripts can be examined simultaneously in situ! Towards the end of the talk, Dr. Boyden highlighted some open questions in the field. These questions focused on a few primary themes: Can we validate expanded samples below 10-20 nm? Is expansion ‘pulling’ synapses apart, leading us to false conclusions? Can we use this technique to probe protein-protein interactions? Whats the smallest thing we can expand? Can we expand a virus? A DNA origami?? How much can we expand a sample while maintaining all relevant spatial relationships? To take the last question, Dr. Boyden’s team reasoned, if we can expand something once, why not twice, or thrice?? They put samples through an iterative process allowing for expansion up to 20x the original size!! (shown below) Iterative Expansion Microscopy allows for sample expansion up to 20x! Panel A shows dendritic spines without expansion, panel B shows the same at 4.5x expansion, and panel C shows dendritic spines at 20x expansion after the iterative process is complete (Credit: Chang et al., 2017; Nature Methods) A cool side effect of expansion is that it involves filling the sample with water, making it essentially transparent, and useful for long-range circuit mapping at high detail or speeding up techniques like light-sheet microscopy. We are only at the surface of what is possible with this and other super-resolution techniques. I look forward to all the exciting things to come! See you guys soon! Feel free to follow me on twitter @jborniger and on my website www.jeremyborniger.com Jeremy C. Borniger, PhD Department of Psychiatry & Behavioral Sciences Stanford University SoM
  3. Techniques and Integrative Physiology and Behavior Highlights I am a neuroscientist funded by the NIH BRAIN Initiative currently working at Stanford University as a post-doc in Luis de Lecea’s Lab. My focus is understanding basic neurocircuitry that controls sleep and wakefulness using optogenetics, calcium imaging, chemogenetics, EEG/EMG, and other strategies. I am further interested in how the brain and periphery communicate, specifically in the context of cancer. I am using mass cytometry approaches to characterize the effects of brain stimulation on the peripheral immune response. 43O2QsVzTcWI2R9nPeF4vw_thumb_c1a.jpg602×1304 260 KB Jeremy C. Borniger, PhD Keep an eye out for my posts on the newest and coolest techniques in the field, as well as more general posts on sleep, circadian rhythms, neuroimmunology, and brain/body communication. Please visit my website for more detail, and follow me on twitter for real time updates during the meeting. I look forward to seeing everyone in San Diego! If you see me, feel free to say hi! Jeremy C Borniger, PhD BRAIN Initiative Postdoctoral Fellow de Lecea lab Department of Psychiatry & Behavioral Sciences Stanford University SoM Twitter: @jborniger NeurOnline: Jeremy_Borniger Website: http://www.jeremyborniger.com Email: jcbornig@stanford.edu
  4. SuperEEG: ECoG data breaks free from electrodes The "gold standard" for measuring neural activity in human brains is ECoG (electrocorticography), using electrodes implanted directly onto the surface of the brain. Unlike methods that measure blood oxygenation (which have poor temporal resolution) or that measure signals on the scalp (which have poor spatial resolution), ECoG data has both high spatial and temporal precision. Most of the ECoG data that has been collected comes from patients who are being treated for epileptic seizures and have had electrodes implanted in order to determine where the seizures are starting. The big problem with ECoG data, however, is that each patient typically only has about 150 implanted electrodes, meaning that we can only measure brain activity in 150 spots (compared to about 100,000 spots for functional MRI). It would seem like there is no way around this - if you don’t measure activity from some part of the brain, then you can’t know anything about what is happening there, right? Actually, you can, or at least you can guess! Lucy Owen, Andrew Heusser, and Jeremy Manning have developed a new analysis tool called SuperEEG, based on the idea that measuring from one region of the brain can actually tell you a lot about another unmeasured region, if the two regions are highly correlated (or anti-correlated). By using many ECoG subjects to learn the correlation structure of the brain, we can extrapolate from measurements in a small set of electrodes to estimate neural activity across the whole brain. Figure from their SfN poster This breaks ECoG data free from little islands of electrodes and allows us to carry out analyses across the brain. Not all brain regions can be well-estimated using this method (due to the typical placement locations of the electrodes and the correlation structure of brain activity), but it works surprisingly well for most of the cortex: Figure from their SfN poster This could also help with the original medical purpose of implanting these electrodes, by allowing doctors to track seizure activity in 3D as it spreads through the brain. It could even be used to help surgeons choose the locations where electrodes should be placed in new patients, to make sure that seizures can be tracked as broadly and accurately as possible.
  5. 1.jpg960×960 106 KB Hello everyone! My name is Chinmaya Sadangi. I completed my PhD from Germany and recently started a postdoc position at the University of Toronto. My background is in Neurodegenerative disorders, Molecular Neuroscience, and Physiology. I am also interested in science communication and photography. My research interest is in Follow my blog posts for updates on themes C and I (Neurodegenerative disorders and Injury and Techniques). I will also be live tweeting for #SfN17 and you can follow me on Twitter to keep up with the updates. Name: Chinmaya Sadangi Position: Postdoctoral Fellow Affiliation: University of Toronto Neuronline: @csadangi Twitter: addictivebrain Webpage: www.theaddictivebrain.wordpress.com
  6. headshot4.JPG1218×1218 419 KB I am currently a postdoc at the Princeton Neuroscience Institute, working with Uri Hasson and Ken Norman, and I will be starting my own research group next summer at Columbia. I study perception and memory for complex, everyday experiences, which I investigate by using naturalistic experiments (such as watching and recalling movies) combined with analysis tools using machine learning. I will be presenting a poster on how our prior knowledge about events shapes neural activity patterns during retrieval on Sunday morning. My SfN blogging will focus on Themes H: Cognition and I: Techniques, especially for human perception and memory. I hope to talk with presenters about both their specific work and what they predict about the future trends in their subfields. My personal blog Follow me @ChrisBaldassano
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