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This brain balancing act allows consciousness
Two types of thinking have a time-sharing deal going on in your brain.
- Your DMN and DAT neural networks cooperate by staying out of each other's way.
- FMRI scans reveal a surprising temporal dance.
- When both systems are at the same activity level, boom, you're unconscious.
While consciousness remains "the hard problem" — as in what exactly is it? Where is it? — a new study published in Science Advances sheds surprising light on how the brain switches us from conscious to unconscious states and vice versa. It has something to do with an imbalance between two neural systems. In fact, consciousness requires that imbalance.
Imagine you and a friend want to go out to dinner but you want Chinese food and your friend wants pizza. If both of your preferences carry equal weight, nobody gets to eat. Let's say that's like unconsciousness. But when one of you gives in, yum: Consciousness.
According to lead author Zirui Huang of University of Michigan Medical School, "Studies have shown that the anti-correlation of the two networks is vital for maintaining ongoing interaction between self and the environment, [and] that contributes to consciousness."
Image source: Gearstd/Shutterstock/Big Think
The two neural networks are the default mode network (DMN) and the dorsal attention network (DAT).
The DMN is an internally directed neural system that exhibits electrical activity in fMRI scans when you're awake and the brain is comparatively at rest and not at work performing a specific task. Maybe you're spacing out, or reflecting on something, or maybe you're enjoying a memory of some sort.
The DAT lights up when your brain is actively directed externally toward accomplishing a specific task; it's sometimes called the "task -positive system."
The scientific term for their relationship is that they're "anti-correlated," and the maintenance of their opposite states is a consistent thing, so some kind of temporal relationship seems implicit.
Image source: Hakaba/Shutterstock
The implied temporal relationship has not previously been definitively shown to impact consciousness. Huang's study, however, tests the idea that this anti-correlation is a requisite for consciousness, or maybe it's the other way around: Absent consciousness, the anti-correlation breaks down.
To test their hypothesis, Huang and his colleagues analyzed resting-state fMRI scans from 98 participants in varying states of responsiveness, located in Shanghai and Wisconsin. (Because participants were given task in various states, the researchers chose to grade their level of unresponsiveness instead of unconsciousness." In addition to a DAT-mode control group, scans were performed on participants who were in unresponsive states from anesthesia, either propofol or ketamine, or from unresponsive wakefulness syndrome, or UWS. Ultimately, the researchers developed four data sets: propofol-Shanghai, propofol-Wisconsin, ketamine, and neuropathological patients.
They found being unresponsive correlated consistently with scans in which the DAT and DMN systems were at equilibrium. No Chinese food or pizza for them.
For confirmation, a second study was performed with scans from 248 subjects published in the OpenfMRI database. The cohort consisted of healthy individuals, as well as individuals with psychiatric disorders including schizophrenia, bipolar disorder, and attention deficit/hyperactivity disorder. Various states of responsiveness in the available scans were identified, and once again, when DAT and DMN activation was equal, participants were in an unresponsive state.
Part of a larger mystery
Image source: John Graner/Wikimedia
Of course, this study doesn't get us much further along regarding the hard problem, but we do now know a little bit more about how consciousness appears to work at least. The DMN and DAT neural networks together account for a lot of what goes on it consciousness. Just, please, not at the same time.
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>
"You dream about these kinds of moments when you're a kid," said lead paleontologist David Schmidt.
- The triceratops skull was first discovered in 2019, but was excavated over the summer of 2020.
- It was discovered in the South Dakota Badlands, an area where the Triceratops roamed some 66 million years ago.
- Studying dinosaurs helps scientists better understand the evolution of all life on Earth.
Credit: David Schmidt / Westminster College<p style="margin-left: 20px;">"We had to be really careful," Schmidt told St. Louis Public Radio. "We couldn't disturb anything at all, because at that point, it was under law enforcement investigation. They were telling us, 'Don't even make footprints,' and I was thinking, 'How are we supposed to do that?'"</p><p>Another difficulty was the mammoth size of the skull: about 7 feet long and more than 3,000 pounds. (For context, the largest triceratops skull ever unearthed was about <a href="https://www.tandfonline.com/doi/abs/10.1080/02724634.2010.483632" target="_blank">8.2 feet long</a>.) The skull of Schmidt's dinosaur was likely a <em>Triceratops prorsus, </em>one of two species of triceratops that roamed what's now North America about 66 million years ago.</p>
Credit: David Schmidt / Westminster College<p>The triceratops was an herbivore, but it was also a favorite meal of the T<em>yrannosaurus rex</em>. That probably explains why the Dakotas contain many scattered triceratops bone fragments, and, less commonly, complete bones and skulls. In summer 2019, for example, a separate team on a dig in North Dakota made <a href="https://www.nytimes.com/2019/07/26/science/triceratops-skull-65-million-years-old.html" target="_blank">headlines</a> after unearthing a complete triceratops skull that measured five feet in length.</p><p>Michael Kjelland, a biology professor who participated in that excavation, said digging up the dinosaur was like completing a "multi-piece, 3-D jigsaw puzzle" that required "engineering that rivaled SpaceX," he jokingly told the <a href="https://www.nytimes.com/2019/07/26/science/triceratops-skull-65-million-years-old.html" target="_blank">New York Times</a>.</p>
Morrison Formation in Colorado
James St. John via Flickr
|Credit: Nobu Tamura/Wikimedia Commons|
Archaeologists discover a cave painting of a wild pig that is now the world's oldest dated work of representational art.
- Archaeologists find a cave painting of a wild pig that is at least 45,500 years old.
- The painting is the earliest known work of representational art.
- The discovery was made in a remote valley on the Indonesian island of Sulawesi.
Oldest Cave Art Found in Sulawesi<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="a9734e306f0914bfdcbe79a1e317a7f0"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/b-wAYtBxn7E?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span>
The Persian polymath and philosopher of the Islamic Golden Age teaches us about self-awareness.