Brain waves guide us in spotlighting surprises

Date:
November 24, 2020
Source:
Picower Institute at MIT
Summary:
Neuroscientists have found that the dynamic interplay of different
brain wave frequencies, rather than dedicated circuitry, appears
to govern the brain's knack for highlighting what's surprising
and downplaying what's predictable.



FULL STORY ==========================================================================
If you open your office door one morning and there is a new package
waiting on your desk, that's what you will notice most in the otherwise unchanged room. A new study by MIT and Boston University neuroscientists
finds that the dynamic interplay of different brain wave frequencies,
rather than dedicated circuitry, appears to govern the brain's knack
for highlighting what's surprising and downplaying what's predictable.


==========================================================================
By measuring thousands of neurons along the surface, or cortex, of the
brain in animals as they reacted to predictable and surprising images,
the researchers observed that low frequency alpha and beta brain waves, or rhythms, originating in the brain's frontal cognitive regions tamped down neural activity associated with predictable stimuli. That paved the way
for neurons in sensory regions in the back of the brain to push forward information associated with unexpected stimuli via higher-frequency
gamma waves. The backflow of alpha/beta carrying inhibitory predictions typically channeled through deeper layers of the cortex, while the
forward flow of excitatory gamma carrying novel stimuli propagated across superficial layers.

"These interactions between beta and gamma are happening all over the
cortex," said Earl Miller, Picower Professor of Neuroscience in the
Department of Brain and Cognitive Sciences at MIT and co-senior author
of the study in Proceedings of the National Academy of Sciences. "And
it's not generic -- it targets the processing of specific stimuli."
In those regards, this new study extends much of Miller's recent work.

Previously his lab at The Picower Institute for Learning and Memory has
shown that in the prefrontal cortex, working memory depends on bursts of
beta rhythms from deep layers regulating gamma frequency activity in more superficial layers. Those findings built, in part, on research published
in 2012 by postdoc Andre' Bastos, who is lead author of the new paper. Now
the new study and another published by Miller's lab earlier this year
suggest that this push and pull between the frequency bands is a common regulatory system of information flow in the cortex. Moreover, the new
results show experimentally that it has a key role in predictive coding
(as Bastos began to theorize in 2012), not just the related function of
working memory.

Predictive coding is a key cognitive function that appears to become
disrupted in autism spectrum disorders, noted Miller and Bastos. Some
people with autism struggle to regard familiar stimuli as such, treating everything as new and equally salient. That can interfere with learning
to recognize predictable situations and therefore the ability to make generalizations about experience.

"Because you are not able to tamp down and actively regulate predicted information, the brain is in a constant state of surging information
forward which can be overwhelming," Bastos said. In fact, for anyone,
he added, being in a completely new place where predictions of the
environment have not yet had time to form can produce a feeling of
sensory overload.



========================================================================== Setting and violating expectations In the study, the team gave animals
a simplified predictive coding experience.

They were presented with an image as a cue, and then after a brief pause
three images returned to the screen including the original. The animals
simply had to direct their gaze to the previously cued image to complete
the task. Sometimes the cue would be the same for many trials on end
(thereby becoming predictable and familiar). Sometimes the cue would
suddenly change, violating the predicted expectation. As animals played
the game, the scientists were reading out neural activity and overall
rhythms produced by that activity in five areas across the cortex, from
visual areas in the back of the head to a parietal cortex in the middle,
to cognitive cortices, including the prefrontal cortex, in the front.

The team wasn't looking to analyze working memory, or how the animals
held the cue image in memory. Instead they were measuring differences
made when the cue image was predictable vs. when it was not. Their
measurements showed that unpredicted stimuli generated more neural
activity than predictable ones. They also revealed that the activity
associated with unpredicted stimuli was strongest in the gamma frequency
band (and the very low frequency theta band), while activity associated
with predicted stimuli was strongest in alpha/beta frequencies.

These changes in power in each frequency weren't across the board --
it was greatest specifically among neurons that responded most to the
presented stimulus. That means that the regulatory changes of brain
waves were acting most strongly on the neural circuitry processing the
cue images the animals were seeing. For this reason, the team refers to
their conceptual model of predictive coding as "predictive routing."
"Our paper shows that predictive coding can work without specialized
circuits for detecting mismatches between predictions and reality,"
Miller said.



========================================================================== Bastos further explained, "The key element of this new model is that
prediction can be accomplished by selectively inhibiting routes of
information flow that carry predictable information." Co-senior author
Nancy Kopell, William Fairfield Warren Distinguished Professor of
Mathematics at Boston University, added, "To be able to support that
idea required the elaborate experiments described in the paper, involving measurements from multiple parts of the brain." Subsequent analysis of
the data also showed other key trends. Among them was that the coherence
of activity between cortical regions was stronger in the alpha/beta
band when the cue image was predictable and stronger in gamma when it
was not. Moreover, the direction of these different bands (how they
propagated back and forth across the cortex) showed that alpha/beta
fed back from higher cognitive) regions to lower (sensory) regions,
while gamma fed forward from lower regions to higher ones.

Paying attention to exceptions The scientists also saw that alpha/beta
mostly peaked in deeper layers of the visual cortices, while gamma often
was strongest in superficial layers. But there were exceptions along the
way. The parietal cortex region 7A bucked the trend of peaking in gamma
for unexpected stimuli, instead peaking in the higher end of the beta
frequency band. One possibility, Kopell says, is that 7A was involved in a working memory buffer, which is believed to use beta oscillations. Another explanation could be that 7A's beta activity is related not to prediction
as much as attention. Animals performing the task did need to pay at least
some degree of attention to the cue, whether it was predictable or not.

Designing experiments that can fully separate attention from prediction
could be an important future direction, Bastos said. Another important
future goal will be to create computational models that simulate
the interactions between layers and frequencies to inhibit predicted information.

"The laminar detail from the current data set will be very useful in
producing such a model," Kopell said.

In addition to Bastos, Miller and Kopell, the paper's other authors are
Mikael Lundqvist and Ayan Waite.

The National Institutes of Mental Health, the Office of Naval Research
and the JPB Foundation funded the study.


========================================================================== Story Source: Materials provided by Picower_Institute_at_MIT. Note:
Content may be edited for style and length.


========================================================================== Journal Reference:
1. Andre' M. Bastos, Mikael Lundqvist, Ayan S. Waite, Nancy Kopell,
Earl K.

Miller. Layer and rhythm specificity for predictive
routing. Proceedings of the National Academy of Sciences, 2020;
202014868 DOI: 10.1073/ pnas.2014868117 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/11/201124092138.htm

--- up 13 weeks, 1 day, 7 hours, 50 minutes
* Origin: -=> Castle Rock BBS <=- Now Husky HPT Powered! (1337:3/111)