Heard about the phenomenon of FNE, or 'first night effect'?
Have you ever woken up in a new place and noted with disappointment that you are still tired?
A new theory suggests that dreams' illogical logic has an important purpose.
Overfitting<p>The goal of machine learning is to supply an algorithm with a data set, a "training set," in which patterns can be recognized and from which predictions that apply to other unseen data sets can be derived.</p><p>If machine learning learns its training set too well, it merely spits out a prediction that precisely — and uselessly — matches that data instead of underlying patterns within it that could serve as predictions likely to be true of other thus-far unseen data. In such a case, the algorithm describes what the data set <em>is</em> rather than what it <em>means</em>. This is called "overfitting."</p><img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNDc4NTQ4Ni9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTY2NDM4NDk1Mn0.bMHbBbt7Nz0vmmQ8fdBKaO-Ycpme5eOCxbjPLEHq9XQ/img.jpg?width=980" id="5049a" class="rm-shortcode" data-rm-shortcode-id="f9a6823125e01f4d69ce13d1eef84486" data-rm-shortcode-name="rebelmouse-image" />
The value of noise<p>To keep machine learning from becoming too fixated on the specific data points in the set being analyzed, programmers may introduce extra, unrelated data as noise or corrupted inputs that are less self-similar than the real data being analyzed.</p><p>This noise typically has nothing to do with the project at hand. It's there, metaphorically speaking, to "distract" and even confuse the algorithm, forcing it to step back a bit to a vantage point at which patterns in the data may be more readily perceived and not drawn from the specific details within the data set.</p><p>Unfortunately, overfitting also occurs a lot in the real world as people race to draw conclusions from insufficient data points — xkcd has a fun example of how this can happen with <a href="https://xkcd.com/1122/" target="_blank">election "facts."</a></p><p>(In machine learning, there's also "underfitting," where an algorithm is too simple to track enough aspects of the data set to glean its patterns.)</p><img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNDc4NTQ5My9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYyMDE5NjY1M30.iS2bq7WEQLeS34zNFPnXwzAZZn9blCyI-KVuXmcHI6o/img.jpg?width=980" id="cd486" class="rm-shortcode" data-rm-shortcode-id="c49cfbbffceb00e3f37f00e0fef859d9" data-rm-shortcode-name="rebelmouse-image" />
Credit: agsandrew/Adobe Stock
Nightly noise<p>There remains a lot we don't know about how much storage space our noggins contain. However, it's obvious that if the brain remembered absolutely everything we experienced in every detail, that would be an awful lot to remember. So it seems the brain consolidates experiences as we dream. To do this, it must make sense of them. It must have a system for figuring out what's important enough to remember and what's unimportant enough to forget rather than just dumping the whole thing into our long-term memory.</p><p>Performing such a wholesale dump would be an awful lot like overfitting: simply documenting what we've experienced without sorting through it to ascertain its meaning.</p><p>This is where the new theory, the <a href="https://arxiv.org/pdf/2007.09560.pdf" target="_blank">Overfitting Brain Hypothesis</a> (OBH) proposed by Erik Hoel of Tufts University, comes in. Suggesting that perhaps the brain's sleeping analysis of experiences is akin to machine learning, he proposes that the illogical narratives in dreams are the biological equivalent of the noise programmers inject into algorithms to keep them from overfitting their data. He says that this may supply just enough off-pattern nonsense to force our brains to see the forest and not the trees in our daily data, our experiences.</p><p>Our experiences, of course, are delivered to us as sensory input, so Hoel suggests that dreams are sensory-input noise, biologically-realistic noise injection with a narrative twist:</p><p style="margin-left: 20px;">"Specifically, there is good evidence that dreams are based on the stochastic percolation of signals through the hierarchical structure of the cortex, activating the default-mode network. Note that there is growing evidence that most of these signals originate in a top-down manner, meaning that the 'corrupted inputs' will bear statistical similarities to the models and representations of the brain. In other words, they are derived from a stochastic exploration of the hierarchical structure of the brain. This leads to the kind structured hallucinations that are common during dreams."</p><p>Put plainly, our dreams are just realistic enough to engross us and carry us along, but are just different enough from our experiences —our "training set" — to effectively serve as noise.</p><p>It's an interesting theory.</p><p>Obviously, we don't know the extent to which our biological mental process actually resemble the comparatively simpler, man-made machine learning. Still, the OBH is worth thinking about, maybe at least more worth thinking about than whatever <em>that</em> was last night.</p>
Getting plenty of sleep just became even more important.
- A new study finds that people without sleep fare better in learning what to fear and not fear than those getting only some sleep.
- Test subjects learned to associate colors with electric shocks, but only some unlearned it.
- The findings could be used to help create new treatments for those at risk of PTSD or anxiety.
Nothing quite like a full night’s rest<p> The <a href="https://www.sciencedirect.com/science/article/abs/pii/S2451902220302822?via%3Dihub" target="_blank" rel="noopener noreferrer">study</a>, titled "Partial and Total Sleep Deprivation Interferes with Neural Correlates of Consolidation of Fear Extinction Memory," was published by a team of researchers from the University of Pittsburgh and Harvard Medical School and can be found in the journal <a href="https://www.journals.elsevier.com/biological-psychiatry-cognitive-neuroscience-and-neuroimaging" target="_blank" rel="noopener noreferrer">Biological Psychiatry: Cognitive Neuroscience and Neuroimaging</a>.</p><p>The researchers split 150 test subjects into three groups. The first got a full night's sleep, the second was "sleep-restricted" to a few hours' rest at the beginning of the night, and the third was utterly sleep deprived. Starting the next morning, they were all subjected to "fear conditioning" and "fear extinction." <br> <br> The conditioning involved participants seeing one of three colors on a screen, two of which were paired with a mild electric shock. The idea being that this teaches a person to begin to develop a fear of that color. Later, the subjects underwent "fear extinction," which had them viewing one of the colors again, but without the shocks. This step is intended to teach subjects that there is no longer a reason to fear that image and that it is now "safe."<br> <br> Later that evening, the test subjects viewed the colors again while having their brains scanned. This allowed the scientists to see if their brains were reacting to the colors with fear despite having "learned" that electric shocks were no longer a threat. <br> <br> Curiously, the brains of those getting no sleep resembled those of the people who enjoyed a full night's rest twelve hours later in that the fear response was absent. Those getting only a few hours of sleep showed signs of fear in their brain activity. This suggests that getting only a little rest might be <em>worse</em> than getting none at all, at least when it comes to learning and unlearning fear responses. </p><p>Brain activity recorded during the tasks painted a similar picture. Those who got a full night's sleep had more activity in the prefrontal cortex, an area tied to emotional regulation. In comparison, those getting only half a night's rest saw more activity in the regions associated with fear. Those getting no sleep had less activity in the fear areas overall. </p><p>The research team suggests that restricted sleeping may lead to a severe reduction in the time we spend in the <a href="https://en.wikipedia.org/wiki/Rapid_eye_movement_sleep" target="_blank" rel="noopener noreferrer">Rapid Eye Movement</a> (REM) phase of sleep. While best known for being the part of the night when we dream, it is also when memories are consolidated. REM tends to occur at the end of 1.5-2 hour periods during sleep. </p>
How can we use this information?<iframe width="730" height="430" src="https://www.youtube.com/embed/1Y-qLKZWyDs" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe><p> This study may help explain why people in high-stress jobs with short sleep schedules, such as emergency response workers, medical professionals, or soldiers, can leave people even more anxious or shell shocked.<br> </p><p>Conceivably, this could be used to help develop new treatments for these conditions. In the meantime, more research is needed before you decide to stay up for a week to avoid developing a phobia. </p>
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The study sheds new light on the relationship between sleep and mental health.
- Poor sleep has been linked to many health problems, including diabetes, heart disease, obesity, depression, anxiety, suicidal thoughts and a shortened lifespan.
- A new study suggests that poor sleep also impairs the brain's ability to suppress unwanted thoughts.
- The researchers suspect this is because not getting enough sleep disrupts the brain's executive control functions.
Study procedures and tasks.
Credit: Harrington et al.<p>The participants were shown faces in either a green or red frame. The green frame indicated "think," meaning the participants should try to remember the image associated with that particular face. In contrast, red meant "no think," make your mind go blank — and if a thought pops up, try to get rid of it.</p><p>Then one group slept for about eight hours, while the other didn't sleep at all. In the morning, both groups completed the think/no-think task. The sleep-deprived group was far less able to keep intrusive thoughts out of their minds, despite the fact that both groups performed equally well the night before in a mock think/no-think task.</p><p style="margin-left: 20px;">"Strikingly, the sleep-deprivation group suffered a proportional increase in intrusions of nearly 50% relative to the sleep group, revealing how deficient control may be a pathway to hyperaccessible thoughts," the researchers wrote.</p><p>As the experiment went along, both groups became increasingly successful at suppressing unwanted thoughts. But the sleep-deprived group was less successful. The results showed a similar effect on relapses of intrusive thoughts (which were prompted by showing the same visual cue multiple times during the experiment): Both groups became better at suppressing relapses over time, but the no-sleep group had a harder time blocking relapses.</p><p style="margin-left: 20px;">"...sleep deprivation diminished the cumulative benefits of retrieval suppression for down-regulating subsequent intrusions," the researchers wrote. "Even after sleep-deprived participants initially gained control over unwanted memories and prevented them from intruding, they were consistently more susceptible to relapses when reminders were confronted again later compared with rested individuals."</p><p>In addition to having difficulty suppressing intrusive thoughts, the sleep-deprived group also seemed to be more negatively affected by those thoughts, based on subjective reports from the participants and skin-conductance responses recorded by the researchers.</p><p>Although the study didn't use brain imaging, the researchers noted that sleep deprivation may impair memory suppression by disrupting functional interactions between various parts of the brain, including "the [dorsolateral prefrontal cortex] (and possibly [medial prefrontal cortex]) and [medial temporal lobe] structures such as the hippocampus and amygdala during retrieval suppression, impairing inhibitory control over memory and affect, increasing intrusions, and decreasing affect suppression."</p>