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Wiring the Brain: How Viruses Can Be Engineered to Trace Neural Connections
The fact that the rabies virus can spread from an infected neuron to other neurons connected to it makes it an almost perfect vector for tracing connections in the brain.
Dr. Kevin Mitchell is a geneticist who studies neural development. In this guest post, he explains how viruses can be used to map connections in the brain.
What's the Big Idea?
It is hard to overstate the complexity of the brain. Not only are there tens of billions of individual nerve cells, or neurons, which make literally trillions ofconnections between each other. The complexity really lies in the fact that there are hundreds or maybe even thousands of different types of neurons, which are arranged in highly-organised patterns, and which connect to each other in very specific ways. Now, a new technique is emerging that enables neuroscientists to trace these kinds of connections by enlisting help from an unlikely source – viruses.
To understand why this approach is so exciting, we need to consider the scope of the problem it can help solve. This begins with individual neurons themselves. Neurons are polarised – they have an end for inputs and an end for outputs. Each of these may be branched to give thousands of independent sites of input and output. For any given neuron, there are other neurons that connect to it (information flows from all those neurons into our subject neuron) and other neurons that it connects to (information flows from our subject neuron out to all these neurons).
But neurons are not all the same. The most obvious and perhaps most important difference between neurons is that some are excitatory and some inhibitory. When an excitatory neuron is activated, it releases neurotransmitter at the connections it makes with its output neurons – this neurotransmitter tends to make those other cells electrically active. The exact opposite happens when an inhibitory cell is activated – it releases a different neurotransmitter onto its target neurons, which makes them less electrically active.
Neurons That Fire Together Wire Together
At any given moment, each single neuron is integrating the incoming information from typically hundreds of excitatory and inhibitory neurons – the balance between these and their precise timing will determine whether it becomes active enough to “fire” a signal to its own output neurons. (Without the inhibitory neurons, any electrical activity would rapidly spread through the entire brain in an epileptic-like firestorm).
There are hundreds of subtypes of excitatory and inhibitory neurons, all with different jobs to do. The way in which these different cell types are interconnected determines the functional properties of each little microcircuit in the brain – the type of information that comes into the system, how it filters and transforms that information, how long a neuron will be active before it's shut off, whether it will fire with a rhythm and at what frequency, etc.
These parameters determine the computations that the circuit can perform. While some of the details of such microcircuits have been worked out, for the most part we remain unblissfully ignorant of this crucial information. But we cannot hope to understand how the brain functions without knowing how the basic units of computation are put together.
How to solve this problem? In looking for ways to map the connections of neurons, scientists are turning to viruses – in particular, those that have evolved to infect neurons and to spread from one to another through the synaptic connections between them. One of these is the deadly rabies virus – a specialist in infecting neurons.
Neural connections in the brain
Rabies is typically transmitted from one infected animal to another through saliva, often via a bite, which releases viral particles that infect peripheral neurons. From there, it spreads backwards into the spinal cord and brain, passing from the initially infected neurons into every neuron that connects to them. This continues in the next neurons, resulting in the rapid spread of infection throughout the enture nervous system. This has a striking effect onthe host – among other symptoms, increasing aggression and attack behaviors, along with salivation, resulting in spread to a new host.
The fact that the virus can spread from an infected neuron to other neuronsconnected to it makes it an almost perfect vector for tracing these connections in the brains of experimental animals. To make it perfect required some modifications.
Modifying the Virus
First, using the tools of molecular biology, researchers have modified the genomeof the rabies virus, so that, as well as its own genes, the virus now carries so-called marker proteins, like the well-known green fluorescent protein from jellyfish. When ultraviolet light is shone on this protein, it fluoresces, giving off avivid green light. Neurons infected with the virus (either directly or via synaptic connections) can thus be beautifully visualised.
A major problem, however, is the rabies virus is too efficient – it continues to spread to all the neurons connected to each of the neurons connected to the first neuron, obscuring the pattern we are interested in. To get around this, the virus had to be crippled by removing one of the genes it needs to spread.
The sequence of the rabies virus genome - which is made from RNA, not DNA - encodes five proteins that are essential for the virus to replicate and be transmitted from one cell to another. When a rabies virus infects a neuron, it starts to express these proteins and replicate its genome. These replicates are packaged into a viral particle, which includes an envelope of host cell membrane studded with viral proteins.
One of these is the rabies glycoprotein, encoded by the G gene. This protein is essential for the viral particle to infect another neuron – it accomplishes this by binding to receptor proteins on the surface ofthese neurons, which leads to it being sucked into the cell (tricksy!).
A Solution: Delete the Genes
Even more tricksy is how scientists have taken advantage of this system to control which cells can be infected and to limit the spread of virus to only one synapse. This involves modifying both the virus and the cells of the host animal (usually a transgenic mouse). First, the G gene can be deleted from the viral genome – these viral particles can infect neurons when the virus is grown ina dish with the G protein added. But after they infect one neuron they cannotspread to others because they can’t make more G protein. The trick is to makethe infected host cell supply that protein – this can be achieved by adding DNA encoding this protein directly into a single cell.
When that single cell is infected, it leads to replication of the virus and transfer to only those cells with directinputs on the primary neuron. Scientists can thus visualise all the inputs ontoa single neuron, and painstakingly reconstruct the connectivity of an entiremicrocircuit.
What's the Significance?
Since the development of these techniques there have been a whole range of further modifications, allowing infection of specific cell types, the tracing of connections in the other direction (to all the output neurons) using different viruses, and the transfer of other cargo proteins to allow all kinds of additional analyses of the functions of these microcircuits.
In combination with tremendous advances in microscopy, these approaches are leading to a resurgence of “descriptive” neuroanatomy – just the kinds of studies that fueled the insights of pioneering neuroscientists like Ramon y Cajal 100 years ago.
Those insights derived from the application of new technologies forvisualising single neurons. These new techniques take us the next step to see themicrocircuits that make up the computational units of the brain.
Northwell Health is using insights from website traffic to forecast COVID-19 hospitalizations two weeks in the future.
- The machine-learning algorithm works by analyzing the online behavior of visitors to the Northwell Health website and comparing that data to future COVID-19 hospitalizations.
- The tool, which uses anonymized data, has so far predicted hospitalizations with an accuracy rate of 80 percent.
- Machine-learning tools are helping health-care professionals worldwide better constrain and treat COVID-19.
The value of forecasting<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTA0Njk2OC9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYyMzM2NDQzOH0.rid9regiDaKczCCKBsu7wrHkNQ64Vz_XcOEZIzAhzgM/img.jpg?width=980" id="2bb93" class="rm-shortcode" data-rm-shortcode-id="31345afbdf2bd408fd3e9f31520c445a" data-rm-shortcode-name="rebelmouse-image" data-width="1546" data-height="1056" />
Northwell emergency departments use the dashboard to monitor in real time.
Credit: Northwell Health<p>One unique benefit of forecasting COVID-19 hospitalizations is that it allows health systems to better prepare, manage and allocate resources. For example, if the tool forecasted a surge in COVID-19 hospitalizations in two weeks, Northwell Health could begin:</p><ul><li>Making space for an influx of patients</li><li>Moving personal protective equipment to where it's most needed</li><li>Strategically allocating staff during the predicted surge</li><li>Increasing the number of tests offered to asymptomatic patients</li></ul><p>The health-care field is increasingly using machine learning. It's already helping doctors develop <a href="https://care.diabetesjournals.org/content/early/2020/06/09/dc19-1870" target="_blank">personalized care plans for diabetes patients</a>, improving cancer screening techniques, and enabling mental health professionals to better predict which patients are at <a href="https://healthitanalytics.com/news/ehr-data-fuels-accurate-predictive-analytics-for-suicide-risk" target="_blank" rel="noopener noreferrer">elevated risk of suicide</a>, to name a few applications.</p><p>Health systems around the world have already begun exploring how <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7315944/" target="_blank" rel="noopener noreferrer">machine learning can help battle the pandemic</a>, including better COVID-19 screening, diagnosis, contact tracing, and drug and vaccine development.</p><p>Cruzen said these kinds of tools represent a shift in how health systems can tackle a wide variety of problems.</p><p>"Health care has always used the past to predict the future, but not in this mathematical way," Cruzen said. "I think [Northwell Health's new predictive tool] really is a great first example of how we should be attacking a lot of things as we go forward."</p>
Making machine-learning tools openly accessible<p>Northwell Health has made its predictive tool <a href="https://github.com/northwell-health/covid-web-data-predictor" target="_blank">available for free</a> to any health system that wishes to utilize it.</p><p>"COVID is everybody's problem, and I think developing tools that can be used to help others is sort of why people go into health care," Dr. Cruzen said. "It was really consistent with our mission."</p><p>Open collaboration is something the world's governments and health systems should be striving for during the pandemic, said Michael Dowling, Northwell Health's president and CEO.</p><p>"Whenever you develop anything and somebody else gets it, they improve it and they continue to make it better," Dowling said. "As a country, we lack data. I believe very, very strongly that we should have been and should be now working with other countries, including China, including the European Union, including England and others to figure out how to develop a health surveillance system so you can anticipate way in advance when these things are going to occur."</p><p>In all, Northwell Health has treated more than 112,000 COVID patients. During the pandemic, Dowling said he's seen an outpouring of goodwill, collaboration, and sacrifice from the community and the tens of thousands of staff who work across Northwell.</p><p>"COVID has changed our perspective on everything—and not just those of us in health care, because it has disrupted everybody's life," Dowling said. "It has demonstrated the value of community, how we help one another."</p>
Scientists used CT scanning and 3D-printing technology to re-create the voice of Nesyamun, an ancient Egyptian priest.
- Scientists printed a 3D replica of the vocal tract of Nesyamun, an Egyptian priest whose mummified corpse has been on display in the UK for two centuries.
- With the help of an electronic device, the reproduced voice is able to "speak" a vowel noise.
- The team behind the "Voices of the Past" project suggest reproducing ancient voices could make museum experiences more dynamic.
Howard et al.<p style="margin-left: 20px;">"While this approach has wide implications for heritage management/museum display, its relevance conforms exactly to the ancient Egyptians' fundamental belief that 'to speak the name of the dead is to make them live again'," they wrote in a <a href="https://www.nature.com/articles/s41598-019-56316-y#Fig3" target="_blank">paper</a> published in Nature Scientific Reports. "Given Nesyamun's stated desire to have his voice heard in the afterlife in order to live forever, the fulfilment of his beliefs through the synthesis of his vocal function allows us to make direct contact with ancient Egypt by listening to a sound from a vocal tract that has not been heard for over 3000 years, preserved through mummification and now restored through this new technique."</p>
Connecting modern people with history<p>It's not the first time scientists have "re-created" an ancient human's voice. In 2016, for example, Italian researchers used software to <a href="https://www.smithsonianmag.com/smart-news/hear-recreated-voice-otzi-iceman-180960570/" target="_blank">reconstruct the voice of Ötzi,</a> an iceman who was discovered in 1991 and is thought to have died more than 5,000 years ago. But the "Voices of the Past" project is different, the researchers note, because Nesyamun's mummified corpse is especially well preserved.</p><p style="margin-left: 20px;">"It was particularly suited, given its age and preservation [of its soft tissues], which is unusual," Howard told <em><a href="https://www.livescience.com/amp/ancient-egypt-mummy-voice-reconstructed.html" target="_blank">Live Science</a>.</em></p><p>As to whether Nesyamun's reconstructed voice will ever be able to speak complete sentences, Howard told <em><a href="https://abcnews.go.com/Weird/wireStory/ancient-voice-scientists-recreate-sound-egyptian-mummy-68482015" target="_blank">The Associated Press</a>, </em>that it's "something that is being worked on, so it will be possible one day."</p><p>John Schofield, an archaeologist at the University of York, said that reproducing voices from history can make museum experiences "more multidimensional."</p><p style="margin-left: 20px;">"There is nothing more personal than someone's voice," he told <em>The Associated Press.</em> "So we think that hearing a voice from so long ago will be an unforgettable experience, making heritage places like Karnak, Nesyamun's temple, come alive."</p>
A new study proposes mysterious axions may be found in X-rays coming from a cluster of neutron stars.
Are Axions Dark Matter?<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="5e35ce24a5b17102bfce5ae6aecc7c14"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/e7yXqF32Yvw?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span>
New research suggests you can't fake your emotional state to improve your work life — you have to feel it.
What is deep acting?<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTQ1NDk2OS9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYxNTY5MzA0Nn0._s7aP25Es1CInq51pbzGrUj3GtOIRWBHZxCBFnbyXY8/img.jpg?width=1245&coordinates=333%2C-1%2C333%2C-1&height=700" id="ddf09" class="rm-shortcode" data-rm-shortcode-id="9dc42c4d6a8e372ad7b72907b46ecd3f" data-rm-shortcode-name="rebelmouse-image" data-width="1245" data-height="700" />
Arlie Russell Hochschild (pictured) laid out the concept of emotional labor in her 1983 book, "The Managed Heart."
Credit: Wikimedia Commons<p>Deep and surface acting are the principal components of emotional labor, a buzz phrase you have likely seen flitting about the Twittersphere. Today, "<a href="https://www.bbc.co.uk/bbcthree/article/5ea9f140-f722-4214-bb57-8b84f9418a7e" target="_blank">emotional labor</a>" has been adopted by groups as diverse as family counselors, academic feminists, and corporate CEOs, and each has redefined it with a patented spin. But while the phrase has splintered into a smorgasbord of pop-psychological arguments, its initial usage was more specific.</p><p>First coined by sociologist Arlie Russell Hochschild in her 1983 book, "<a href="https://www.ucpress.edu/book/9780520272941/the-managed-heart" target="_blank">The Managed Heart</a>," emotional labor describes the work we do to regulate our emotions on the job. Hochschild's go-to example is the flight attendant, who is tasked with being "nicer than natural" to enhance the customer experience. While at work, flight attendants are expected to smile and be exceedingly helpful even if they are wrestling with personal issues, the passengers are rude, and that one kid just upchucked down the center aisle. Hochschild's counterpart to the flight attendant is the bill collector, who must instead be "nastier than natural."</p><p>Such personas may serve an organization's mission or commercial interests, but if they cause emotional dissonance, they can potentially lead to high emotional costs for the employee—bringing us back to deep and surface acting.</p><p>Deep acting is the process by which people modify their emotions to match their expected role. Deep actors still encounter the negative emotions, but they devise ways to <a href="http://www.selfinjury.bctr.cornell.edu/perch/resources/what-is-emotion-regulationsinfo-brief.pdf" target="_blank">regulate those emotions</a> and return to the desired state. Flight attendants may modify their internal state by talking through harsh emotions (say, with a coworker), focusing on life's benefits (next stop Paris!), physically expressing their desired emotion (smiling and deep breaths), or recontextualizing an inauspicious situation (not the kid's fault he got sick).</p><p>Conversely, surface acting occurs when employees display ersatz emotions to match those expected by their role. These actors are the waiters who smile despite being crushed by the stress of a dinner rush. They are the CEOs who wear a confident swagger despite feelings of inauthenticity. And they are the bouncers who must maintain a steely edge despite humming show tunes in their heart of hearts.</p><p>As we'll see in the research, surface acting can degrade our mental well-being. This deterioration can be especially true of people who must contend with negative emotions or situations inside while displaying an elated mood outside. Hochschild argues such emotional labor can lead to exhaustion and self-estrangement—that is, surface actors erect a bulwark against anger, fear, and stress, but that disconnect estranges them from the emotions that allow them to connect with others and live fulfilling lives.</p>
Don't fake it till you make it<p>Most studies on emotional labor have focused on customer service for the obvious reason that such jobs prescribe emotional states—service with a smile or, if you're in the bouncing business, a scowl. But <a href="https://eller.arizona.edu/people/allison-s-gabriel" target="_blank">Allison Gabriel</a>, associate professor of management and organizations at the University of Arizona's Eller College of Management, wanted to explore how employees used emotional labor strategies in their intra-office interactions and which strategies proved most beneficial.</p><p>"What we wanted to know is whether people choose to engage in emotion regulation when interacting with their co-workers, why they choose to regulate their emotions if there is no formal rule requiring them to do so, and what benefits, if any, they get out of this effort," Gabriel said in <a href="https://www.sciencedaily.com/releases/2020/01/200117162703.htm" target="_blank">a press release</a>.</p><p>Across three studies, she and her colleagues surveyed more than 2,500 full-time employees on their emotional regulation with coworkers. The survey asked participants to agree or disagree with statements such as "I try to experience the emotions that I show to my coworkers" or "I fake a good mood when interacting with my coworkers." Other statements gauged the outcomes of such strategies—for example, "I feel emotionally drained at work." Participants were drawn from industries as varied as education, engineering, and financial services.</p><p>The results, <a href="https://psycnet.apa.org/doiLanding?doi=10.1037%2Fapl0000473" target="_blank" rel="noopener noreferrer">published in the Journal of Applied Psychology</a>, revealed four different emotional strategies. "Deep actors" engaged in high levels of deep acting; "low actors" leaned more heavily on surface acting. Meanwhile, "non-actors" engaged in negligible amounts of emotional labor, while "regulators" switched between both. The survey also revealed two drivers for such strategies: prosocial and impression management motives. The former aimed to cultivate positive relationships, the latter to present a positive front.</p><p>The researchers found deep actors were driven by prosocial motives and enjoyed advantages from their strategy of choice. These actors reported lower levels of fatigue, fewer feelings of inauthenticity, improved coworker trust, and advanced progress toward career goals. </p><p>As Gabriel told <a href="https://www.psypost.org/2021/01/new-psychology-research-suggests-deep-acting-can-reduce-fatigue-and-improve-your-work-life-59081" target="_blank" rel="noopener noreferrer">PsyPost in an interview</a>: "So, it's a win-win-win in terms of feeling good, performing well, and having positive coworker interactions."</p><p>Non-actors did not report the emotional exhaustion of their low-actor peers, but they also didn't enjoy the social gains of the deep actors. Finally, the regulators showed that the flip-flopping between surface and deep acting drained emotional reserves and strained office relationships.</p><p>"I think the 'fake it until you make it' idea suggests a survival tactic at work," Gabriel noted. "Maybe plastering on a smile to simply get out of an interaction is easier in the short run, but long term, it will undermine efforts to improve your health and the relationships you have at work. </p><p>"It all boils down to, 'Let's be nice to each other.' Not only will people feel better, but people's performance and social relationships can also improve."</p>
You'll be glad ya' decided to smile<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="88a0a6a8d1c1abfcf7b1aca8e71247c6"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/QOSgpq9EGSw?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span><p>But as with any research that relies on self-reported data, there are confounders here to untangle. Even during anonymous studies, participants may select socially acceptable answers over honest ones. They may further interpret their goal progress and coworker interactions more favorably than is accurate. And certain work conditions may not produce the same effects, such as toxic work environments or those that require employees to project negative emotions.</p><p>There also remains the question of the causal mechanism. If surface acting—or switching between surface and deep acting—is more mentally taxing than genuinely feeling an emotion, then what physiological process causes this fatigue? <a href="https://www.frontiersin.org/articles/10.3389/fnhum.2019.00151/full" target="_blank">One study published in the <em>Frontiers in Human Neuroscience</em></a><em> </em>measured hemoglobin density in participants' brains using an fNIRS while they expressed emotions facially. The researchers found no significant difference in energy consumed in the prefrontal cortex by those asked to deep act or surface act (though, this study too is limited by a lack of real-life task).<br></p><p>With that said, Gabriel's studies reinforce much of the current research on emotional labor. <a href="https://journals.sagepub.com/doi/abs/10.1177/2041386611417746" target="_blank">A 2011 meta-analysis</a> found that "discordant emotional labor states" (read: surface acting) were associated with harmful effects on well-being and performance. The analysis found no such consequences for deep acting. <a href="https://doi.apa.org/doiLanding?doi=10.1037%2Fa0022876" target="_blank" rel="noopener noreferrer">Another meta-analysis</a> found an association between surface acting and impaired well-being, job attitudes, and performance outcomes. Conversely, deep acting was associated with improved emotional performance.</p><p>So, although there's still much to learn on the emotional labor front, it seems Van Dyke's advice to a Leigh was half correct. We should put on a happy face, but it will <a href="https://bigthink.com/design-for-good/everything-you-should-know-about-happiness-in-one-infographic" target="_self">only help if we can feel it</a>.</p>
Archaeologists discover a cave painting of a wild pig that is now the world's oldest dated work of representational art.