Q: How would creatures survive without it for eons WAITING for it to evolve?...If you could survive without it--why evolve it?
I will praise Thee; for I am fearfully and wonderfully made: marvelous are Thy works; Psalm 139:14
"January 2020, Janna Lendner presented findings that hint at a way to look at people’s brain activity for signs of the boundary between
wakefulness and unconsciousness.
Lendner argued, though, that the answer isn’t in the regular brain waves, but rather in an aspect of neural activity that scientists might normally ignore: the erratic background noise.
Some researchers seemed incredulous. “They said, ‘So, you’re telling
me that there’s, like, information in the noise?’” said Lendner, an anesthesiology resident at the University Medical Center in Tübingen, Germany, who recently completed a postdoc at the University of California, Berkeley. “I said, ‘Yes. Someone’s noise is another one’s signal.’”
Lendner is one of a growing number of neuroscientists energized by
the idea that noise in the brain’s electrical activity could hold new clues to its inner workings.
Voytek developed software that isolates regular oscillations — like alpha waves, which are studied heavily in both sleeping and waking subjects — hiding in the aperiodic parts of brain activity.
The phenomenon that Voytek and other scientists are investigating in a variety of ways goes by many names. Some call it “the 1/f slope” or “scale-free activity”; Voytek has pushed to rebrand it “the aperiodic signal” or “aperiodic activity.”
Our bodies groove to the familiar rhythms of heartbeats and breaths — persistent cycles essential to survival. But there are equally vital drumbeats in the brain that don’t seem to have a pattern, and they may contain new clues to the underpinnings of behavior and cognition.
When a neuron sends a chemical called glutamate to another neuron,
it makes the recipient more likely to fire; this scenario is called excitation.
Conversely, if a neuron spits out the neurotransmitter gamma-aminobutyric acid, or GABA, the recipient neuron becomes less likely to fire; that’s inhibition.
Too much of either has consequences:
---Excitation gone haywire leads to seizures,
---while inhibition characterizes sleep and, in more extreme cases, coma.
To study the delicate balance between excitation and inhibition, scientists measure the brain’s electrical activity with
electroencephalography, or EEG. Cycles in excitation and inhibition form waves that have been linked to different mental states. Brain emissions at around 8 to 12 hertz, for example, form the alpha wave pattern associated with sleep.
But the brain’s electrical output doesn’t produce perfectly smooth curves. Instead, the lines jitter as they slope up toward peaks and down toward troughs. Sometimes brain activity has no regularity and instead looks more like electrical noise. The “white noise” component of this is truly random like static, but some of it has a more interesting statistical structure.
Awareness of the 1/f phenomenon dates back to a 1925 paper by J.B. Johnson of Bell Telephone Laboratories, who was looking at noise in vacuum tubes. The German scientist Hans Berger published the first human EEG study just four years later. Neuroscience research in subsequent decades focused heavily on the prominent periodic waves in brain activity. Yet 1/f fluctuations were found in all kinds of electrical noise, stock market activity, biological rhythms, and even pieces of music — and no one knew why.
Lendner and her colleagues found that in the aperiodic noise of test subjects’ EEGs, the high-frequency activity dropped off faster during REM sleep than when they were awake. In other words, the slope of the power spectrum was steeper......One theory is that aperiodic signals somehow reflect the delicate balance between excitation and inhibition that the brain needs to keep itself healthy and active.
*An alternative idea is that the aperiodic signals simply reflect the brain’s physical organization. Based on how other physical systems reflect 1/f behaviors, Ward thinks there could be some kind of structural, hierarchical relationship in the brain that gives rise to the aperiodic activity.
"January 2020, Janna Lendner presented findings that hint at a way to look at people’s brain activity for signs of the boundary between
For patients who are comatose or under anesthesia, it can be all-important that physicians make that distinction correctly. Doing so is trickier than it might sound, however, because when someone is in the dreaming state of rapid-eye movement (REM) sleep, their brain produces the same familiar, smoothly oscillating brain waves as when they are awake.
Lendner argued, though, that the answer isn’t in the regular brain waves, but rather in an aspect of neural activity that scientists might normally ignore: the erratic background noise.
Some researchers seemed incredulous. “They said, ‘So, you’re telling
me that there’s, like, information in the noise?’” said Lendner, an anesthesiology resident at the University Medical Center in Tübingen, Germany, who recently completed a postdoc at the University of California, Berkeley. “I said, ‘Yes. Someone’s noise is another one’s signal.’”
Lendner is one of a growing number of neuroscientists energized by
Voytek developed software that isolates regular oscillations — like alpha waves, which are studied heavily in both sleeping and waking subjects — hiding in the aperiodic parts of brain activity.
The phenomenon that Voytek and other scientists are investigating in a variety of ways goes by many names. Some call it “the 1/f slope” or “scale-free activity”; Voytek has pushed to rebrand it “the aperiodic signal” or “aperiodic activity.”
Our bodies groove to the familiar rhythms of heartbeats and breaths — persistent cycles essential to survival. But there are equally vital drumbeats in the brain that don’t seem to have a pattern, and they may contain new clues to the underpinnings of behavior and cognition.
When a neuron sends a chemical called glutamate to another neuron,
Conversely, if a neuron spits out the neurotransmitter gamma-aminobutyric acid, or GABA, the recipient neuron becomes less likely to fire; that’s inhibition.
Too much of either has consequences:
---Excitation gone haywire leads to seizures,
---while inhibition characterizes sleep and, in more extreme cases, coma.
To study the delicate balance between excitation and inhibition, scientists measure the brain’s electrical activity with
electroencephalography, or EEG. Cycles in excitation and inhibition form waves that have been linked to different mental states. Brain emissions at around 8 to 12 hertz, for example, form the alpha wave pattern associated with sleep.
But the brain’s electrical output doesn’t produce perfectly smooth curves. Instead, the lines jitter as they slope up toward peaks and down toward troughs. Sometimes brain activity has no regularity and instead looks more like electrical noise. The “white noise” component of this is truly random like static, but some of it has a more interesting statistical structure.
Awareness of the 1/f phenomenon dates back to a 1925 paper by J.B. Johnson of Bell Telephone Laboratories, who was looking at noise in vacuum tubes. The German scientist Hans Berger published the first human EEG study just four years later. Neuroscience research in subsequent decades focused heavily on the prominent periodic waves in brain activity. Yet 1/f fluctuations were found in all kinds of electrical noise, stock market activity, biological rhythms, and even pieces of music — and no one knew why.
Lendner and her colleagues found that in the aperiodic noise of test subjects’ EEGs, the high-frequency activity dropped off faster during REM sleep than when they were awake. In other words, the slope of the power spectrum was steeper......One theory is that aperiodic signals somehow reflect the delicate balance between excitation and inhibition that the brain needs to keep itself healthy and active.
Too much excitation may overload the brain,
while too much inhibition may put it to sleep.
*An alternative idea is that the aperiodic signals simply reflect the brain’s physical organization. Based on how other physical systems reflect 1/f behaviors, Ward thinks there could be some kind of structural, hierarchical relationship in the brain that gives rise to the aperiodic activity.
For example, this might arise from the way that huge numbers of neurons organize themselves into groups, which then form larger regions that work together."
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