It’s
been over 20 years since neuroimaging studies – using functional
magnetic resonance imaging (fMRI), a widely-used technology to capture
live videos of brain activity – have been detecting brain-wide complex
patterns of correlated brain activity that appear disrupted in a wide
range of neurological and psychiatric disorders. These patterns form
spontaneously, even at rest when no particular task is being performed,
and have been detected not only in humans but also across mammals,
including monkeys and rodents.
Although such spatial patterns of correlated activation have been
consistently detected across neuroimaging centers around the world, the
nature of these correlations was not clear. “We do not yet fully
understand how the brain communicates over long distances. We know that
distant areas exhibit signal correlations, and that they are implicated
in brain function, but we do not completely understand their nature”,
says the senior author of a study published in the journal Nature Communications.
“In this study, we wanted to understand what lies underneath those
correlations and investigate the mechanisms involved”, stresses the
author.
A number of theoretical works had proposed that these patterns could be
explained by standing waves (whose peaks and troughs do not move in
space) resonating in the brain structure – that is, by waves analogous
to the modes of vibration in musical instruments. But there was little
experimental evidence to support this hypothesis due to the poor
temporal resolution of fMRI, reaching only an image or two per second.
“If we could find that the spatial patterns oscillate, this would
provide evidence supporting the resonance hypothesis” says the first
author of the study.
So what the team did was to speed up image acquisition, and they
discovered that the signals in distant brain regions actually oscillate
together in time. “These oscillatory patterns look like a
higher-dimensional analogue of resonance modes in musical instruments;
they are akin to reverberations, to echoes inside the brain”, says the
author.
“Our data show that the complex spatial patterns are a result of
transiently and independently oscillating underlying modes, just like
individual instruments participate in creating a more complex piece in
an orchestra”, says the senior author. “The distinct modes, each
contributing something to the overall picture at different time scales
and different wavelengths, can be added up together, generating complex
macroscopic patterns similar to the ones observed experimentally. To our
knowledge, this is the first time that brain activity captured with
fMRI is reconstructed as the superposition of standing waves”, the
author points out.
The new study thus strongly points to a key role for these resonant
waves, or modes, in brain function. These resonant phenomena, the
authors believe, are at the root of the coherent, coordinated brain
activity that is needed for normal brain function as a whole.
The researchers detected the resonant modes in rats in the resting
state, which means the animals were not subjected to any specific
external stimulus. Indeed, no tasks were needed, for as already
mentioned, even when we (and mammals in general) are doing nothing in
particular, our brains continue to generate spontaneous activity
patterns that can be captured by fMRI.
To visualise the oscillations, the researchers created “videos” of
activity using the potent ultrahigh-field experimental MRI scanner in
the lab and performed ultrafast experiments developed some time ago by
that lab for other purposes.
“When we first saw the videos of the recorded brain activity, we saw
clear waves of activity, like waves in the ocean, propagating in complex
patterns within the cortex and the striatum [a subcortical region of
the forebrain]”, says the first author. “And we found that the signals
could be described by the superposition of a small number of macroscopic
stationary waves, or resonant modes, oscillating in time. Notably, each
standing wave was found to cover extended areas of the brain, with
peaks distributed in distinct cortical and subcortical structures,
forming functional networks.”
The researchers experimented with rats in three different conditions:
sedated, lightly anesthetised and deeply anesthetised. (In fact, the
animals were lightly sedated in the resting state, to avoid any
discomfort to them.) “The spatial configuration of these stationary
waves was very consistent across rats scanned in the same condition”,
the author points out.
The senior author adds: “We showed that brain functional networks are
driven by resonance phenomena. This explains the correlations that are
otherwise observed when you do slow imaging. Long-range brain
interactions are governed by a ‘flow’ of information that is oscillatory
and repetitive.”
They also found that increasing the amount of anesthetic reduces the
number, frequency and duration of the resonant stationary waves. As
already mentioned, previous studies have shown that certain patterns of
brain activation are consistently altered in disorders of
consciousness. So this experimental design, says Cabral, was actually
also meant to mimic different pathological states.
“Functional networks appear disrupted in several neurological and
psychiatric disorders” the author points out. If confirmed in humans,
their results could also lead to the use of resonant modes as
biomarkers for disease.
“Our study also provides a new ‘lead’ in looking at disease”,
corroborates the senior author. “We know that long-range brain activity
is strongly impacted in disease, but we do not understand why or how.
Understanding the mechanism of long-range interactions could lead to a
completely new way of characterising disease and hinting on the type of
treatment that may be necessary: for example, if a specific resonant
mode was missing from a patient, we might want to find ways to stimulate
that particular mode.”
More work will obviously be needed to confirm all these results, the
researchers agree, and whether they are replicable in humans. But “once
we understand better the nature of functional networks, we can design
informed strategies to modulate these network patterns”, says the first
author.
https://www.nature.com/articles/s41467-023-36025-x
http://sciencemission.com/site/index.php?page=news&type=view&id=publications%2Fintrinsic-macroscale&filter=22