• Singing in the brain

    From ScienceDaily@1:317/3 to All on Tue Feb 22 21:31:36 2022
    Singing in the brain
    Neuroscientists have identified a population of neurons in the human
    brain that respond to singing but not other types of music.

    Date:
    February 22, 2022
    Source:
    Massachusetts Institute of Technology
    Summary:
    For the first time, neuroscientists have identified a population
    of neurons in the human brain that light up when we hear singing,
    but not other types of music.



    FULL STORY ==========================================================================
    For the first time, MIT neuroscientists have identified a population of
    neurons in the human brain that lights up when we hear singing, but not
    other types of music.


    ========================================================================== These neurons, found in the auditory cortex, appear to respond to the
    specific combination of voice and music, but not to either regular speech
    or instrumental music. Exactly what they are doing is unknown and will
    require more work to uncover, the researchers say.

    "The work provides evidence for relatively fine-grained segregation
    of function within the auditory cortex, in a way that aligns with an
    intuitive distinction within music," says Sam Norman-Haignere, a former
    MIT postdoc who is now an assistant professor of neuroscience at the
    University of Rochester Medical Center.

    The work builds on a 2015 study in which the same research team used
    functional magnetic resonance imaging (fMRI) to identify a population
    of neurons in the brain's auditory cortex that responds specifically to
    music. In the new work, the researchers used recordings of electrical
    activity taken at the surface of the brain, which gave them much more
    precise information than fMRI.

    "There's one population of neurons that responds to singing, and then
    very nearby is another population of neurons that responds broadly to
    lots of music.

    At the scale of fMRI, they're so close that you can't disentangle them,
    but with intracranial recordings, we get additional resolution, and that's
    what we believe allowed us to pick them apart," says Norman-Haignere.

    Norman-Haignere is the lead author of the study, which appears
    today in the journal Current Biology. Josh McDermott, an associate
    professor of brain and cognitive sciences, and Nancy Kanwisher, the
    Walter A. Rosenblith Professor of Cognitive Neuroscience, both members
    of MIT's McGovern Institute for Brain Research and Center for Brains,
    Minds and Machines (CBMM), are the senior authors of the study.



    ========================================================================== Neural recordings In their 2015 study, the researchers used fMRI to scan
    the brains of participants as they listened to a collection of 165 sounds, including different types of speech and music, as well as everyday sounds
    such as finger tapping or a dog barking. For that study, the researchers devised a novel method of analyzing the fMRI data, which allowed them
    to identify six neural populations with different response patterns,
    including the music-selective population and another population that
    responds selectively to speech.

    In the new study, the researchers hoped to obtain higher-resolution data
    using a technique known as electrocorticography (ECoG), which allows
    electrical activity to be recorded by electrodes placed inside the
    skull. This offers a much more precise picture of electrical activity
    in the brain compared to fMRI, which measures blood flow in the brain
    as a proxy of neuron activity.

    "With most of the methods in human cognitive neuroscience, you can't
    see the neural representations," Kanwisher says. "Most of the kind
    of data we can collect can tell us that here's a piece of brain that
    does something, but that's pretty limited. We want to know what's
    represented in there." Electrocorticography cannot be typically be
    performed in humans because it is an invasive procedure, but it is often
    used to monitor patients with epilepsy who are about to undergo surgery
    to treat their seizures. Patients are monitored over several days so
    that doctors can determine where their seizures are originating before operating. During that time, if patients agree, they can participate
    in studies that involve measuring their brain activity while performing
    certain tasks. For this study, the MIT team was able to gather data from
    15 participants over several years.



    ==========================================================================
    For those participants, the researchers played the same set of 165
    sounds that they used in the earlier fMRI study. The location of each
    patient's electrodes was determined by their surgeons, so some did not
    pick up any responses to auditory input, but many did. Using a novel statistical analysis that they developed, the researchers were able to
    infer the types of neural populations that produced the data that were
    recorded by each electrode.

    "When we applied this method to this data set, this neural response
    pattern popped out that only responded to singing," Norman-Haignere
    says. "This was a finding we really didn't expect, so it very much
    justifies the whole point of the approach, which is to reveal potentially
    novel things you might not think to look for." That song-specific
    population of neurons had very weak responses to either speech or
    instrumental music, and therefore is distinct from the music- and speech-selective populations identified in their 2015 study.

    Music in the brain In the second part of their study, the researchers
    devised a mathematical method to combine the data from the intracranial recordings with the fMRI data from their 2015 study. Because fMRI can
    cover a much larger portion of the brain, this allowed them to determine
    more precisely the locations of the neural populations that respond
    to singing.

    "This way of combining ECoG and fMRI is a significant methodological
    advance," McDermott says. "A lot of people have been doing ECoG over the
    past 10 or 15 years, but it's always been limited by this issue of the
    sparsity of the recordings. Sam is really the first person who figured
    out how to combine the improved resolution of the electrode recordings
    with fMRI data to get better localization of the overall responses."
    The song-specific hotspot that they found is located at the top of
    the temporal lobe, near regions that are selective for language and
    music. That location suggests that the song-specific population may be responding to features such as the perceived pitch, or the interaction
    between words and perceived pitch, before sending information to other
    parts of the brain for further processing, the researchers say.

    The researchers now hope to learn more about what aspects of singing drive
    the responses of these neurons. They are also working with MIT Professor Rebecca Saxe's lab to study whether infants have music-selective areas,
    in hopes of learning more about when and how these brain regions develop.

    The research was funded by the National Institutes of Health, the
    U.S. Army Research Office, the National Science Foundation, the NSF
    Science and Technology Center for Brains, Minds, and Machines, the
    Fondazione Neurone, and the Howard Hughes Medical Institute.

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    Massachusetts_Institute_of_Technology. Original written by Anne
    Trafton. Note: Content may be edited for style and length.


    ========================================================================== Journal Reference:
    1. Sam V. Norman-Haignere, Jenelle Feather, Dana Boebinger, Peter
    Brunner,
    Anthony Ritaccio, Josh H. Mcdermott, Gerwin Schalk, Nancy
    Kanwisher. A neural population selective for song in human auditory
    cortex. Current Biology, 2022 DOI: 10.1016/j.cub.2022.01.069 ==========================================================================

    Link to news story: https://www.sciencedaily.com/releases/2022/02/220222121221.htm

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