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Developmental biology - Brain function|
Making sense of sight and sound
"A computational advantage of this scheme is that it allows the brain to easily build on previous content to learn novel information."
Their study, published in Neuron, is the first to provide strong evidence that learning along vision and auditory paths follows similar principles. "We have long tried to make sense of senses, studying how the brain represents our multisensory world," says Riesenhuber.
In 2007, the same investigators were first to describe the two-step model in human learning of visual categories, and the new study now shows that the brain appears to use the same kind of learning mechanisms across sensory modalities.
Joseph Rauschecker PhD, Department of Neuroscience, Georgetown University Medical Center, Washington, DC, and Institute for Advanced Study, Technische Universität München, Germany, one of the co-authors, believes their findings could help scientists devise new approaches to restore sensory deficits. Rauschecker: "Knowing how senses learn the world may help us devise workarounds in our very plastic brains," he says. "If a person can't process one sensory modality, say vision due to blindness, there could be substitution devices that allow visual input to be transformed into sound. So one disabled sense would be processed by another sensory brain center."
The 16 participants in this study were trained to categorize monkey communication calls - sounds that mean something to monkeys, but are alien in meaning to humans. The investigators divided the sounds into two categories labeled with nonsense names, based on prototypes from two categories: so-called "coos" and "harmonic arches." Using an auditory morphing system, the investigators were able to create thousands of monkey call combinations from the prototypes, including some very similar calls that required the participants to make fine distinctions between the calls. Learning to correctly categorize the novel sounds took about six hours.
Before and after training, fMRI data obtained from volunteers helped investigate changes in neuronal tuning induced by categorization training. Advanced fMRI techniques, functional magnetic resonance imaging rapid adaptation (fMRI-RA) and multi-voxel pattern analysis, were used along with conventional fMRI and functional connectivity analyses. In this way, researchers could distinguish sets of changes: a representation of monkey calls in the left auditory cortex, and tuning analysis that leads to category selectivity of different calls in the lateral prefrontal cortex.
"In our study, we used four different techniques, in particular fMRI-RA and MVPA, to independently and synergistically provide converging results. This allowed us to obtain strong results even from a small sample."
Processing sound requires discrimination in acoustics and tuning changes at the auditory cortex level, a process that researchers say is the same in humans as in animal communication systems. Using monkey calls instead of human speech forced participants to categorize sounds purely on the basis of acoustics rather than meaning.
"At an evolutionary level, humans and animals need to understand who is friend and who is foe, and sight and sound are integral to these judgments," Riesenhuber points out.
• Human subjects learned to categorize morphed monkey calls • Training sharpened neural selectivity to auditory features in left auditory cortex • Training induced auditory category selectivity in lateral prefrontal cortex • This indicates similar principles of learning in the visual and auditory domains
Grouping auditory stimuli into common categories is essential for a variety of auditory tasks, including speech recognition. We trained human participants to categorize auditory stimuli from a large novel set of morphed monkey vocalizations. Using fMRI-rapid adaptation (fMRI-RA) and multi-voxel pattern analysis (MVPA) techniques, we gained evidence that categorization training results in two distinct sets of changes: sharpened tuning to monkey call features (without explicit category representation) in left auditory cortex and category selectivity for different types of calls in lateral prefrontal cortex. In addition, the sharpness of neural selectivity in left auditory cortex, as estimated with both fMRI-RA and MVPA, predicted the steepness of the categorical boundary, whereas categorical judgment correlated with release from adaptation in the left inferior frontal gyrus. These results support the theory that auditory category learning follows a two-stage model analogous to the visual domain, suggesting general principles of perceptual category learning in the human brain.
Authors:Xiong Jiang, Mark A. Chevillet, Josef P. Rauschecker, Maximilian Riesenhuber, Maximilian Riesenhuber
The work was supported by grant from the National Science Foundation (BCS 0749986).
Authors report having no personal financial interests related to the study.
About Georgetown University Medical Center
Georgetown University Medical Center (GUMC) is an internationally recognized academic medical center with a three-part mission of research, teaching and patient care (through MedStar Health). GUMC's mission is carried out with a strong emphasis on public service and a dedication to the Catholic, Jesuit principle of cura personalis -- or "care of the whole person." The Medical Center includes the School of Medicine and the School of Nursing & Health Studies, both nationally ranked; Georgetown Lombardi Comprehensive Cancer Center, designated as a comprehensive cancer center by the National Cancer Institute; and the Biomedical Graduate Research Organization, which accounts for the majority of externally funded research at GUMC including a Clinical and Translational Science Award from the National Institutes of Health. Connect with GUMC on Facebook (Facebook.com/GUMCUpdate), Twitter (@gumedcenter) and Instagram (@gumedcenter).
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Sixteen participants in this study were trained to categorize monkey communication calls - sounds that mean something to monkeys, but are alien in meaning to humans. Using two other techniques in addition to fMRI-RA and MVPA, the study was able to obtain strong results even from their small sample.
Image credit: Public domain composite.