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It has been postulated that the brain is organized by “metamodal,” sensory-independent cortical modules capable of performing tasks (e.g., word recognition) in both “standard” and novel sensory modalities. Still, this theory has primarily been tested in sensory-deprived individuals, with mixed evidence in neurotypical subjects, thereby limiting its support as a general principle of brain organization. Critically, current theories of metamodal processing do not specify requirements for successful metamodal processing at the level of neural representations. Specification at this level may be particularly important in neurotypical individuals, where novel sensory modalities must interface with existing representations for the standard sense. Here we hypothesized that effective metamodal engagement of a cortical area requires congruence between stimulus representations in the standard and novel sensory modalities in that region. To test this, we first used fMRI to identify bilateral auditory speech representations. We then trained 20 human participants (12 female) to recognize vibrotactile versions of auditory words using one of two auditory-to-vibrotactile algorithms. The vocoded algorithm attempted to match the encoding scheme of auditory speech while the token-based algorithm did not. Crucially, using fMRI, we found that only in the vocoded group did trained-vibrotactile stimuli recruit speech representations in the superior temporal gyrus and lead to increased coupling between them and somatosensory areas. Our results advance our understanding of brain organization by providing new insight into unlocking the metamodal potential of the brain, thereby benefitting the design of novel sensory substitution devices that aim to tap into existing processing streams in the brain. SIGNIFICANCE STATEMENTIt has been proposed that the brain is organized by “metamodal,” sensory-independent modules specialized for performing certain tasks. This idea has inspired therapeutic applications, such as sensory substitution devices, for example, enabling blind individuals “to see” by transforming visual input into soundscapes. Yet, other studies have failed to demonstrate metamodal engagement. Here, we tested the hypothesis that metamodal engagement in neurotypical individuals requires matching the encoding schemes between stimuli from the novel and standard sensory modalities. We trained two groups of subjects to recognize words generated by one of two auditory-to-vibrotactile transformations. Critically, only vibrotactile stimuli that were matched to the neural encoding of auditory speech engaged auditory speech areas after training. This suggests that matching encoding schemes is critical to unlocking the brain's metamodal potential.
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Sparse connectivity for MAP inference in linear models using sister mitral cells
Sensory processing is hard because the variables of interest are encoded in spike trains in a relatively complex way. A major goal in studies of sensory processing is to understand how the brain extracts those variables. Here we revisit a common encoding model in which variables are encoded linearly. Although there are typically more variables than neurons, this problem is still solvable because only a small number of variables appear at any one time (sparse prior). However, previous solutions require all-to-all connectivity, inconsistent with the sparse connectivity seen in the brain. Here we propose an algorithm that provably reaches the MAP (maximuma posteriori) inference solution, but does so using sparse connectivity. Our algorithm is inspired by the circuit of the mouse olfactory bulb, but our approach is general enough to apply to other modalities. In addition, it should be possible to extend it to nonlinear encoding models.
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- Award ID(s):
- 2014217
- PAR ID:
- 10491833
- Editor(s):
- Kiebel, Stefan
- Publisher / Repository:
- PLOS Computational Biology
- Date Published:
- Journal Name:
- PLOS Computational Biology
- Volume:
- 18
- Issue:
- 1
- ISSN:
- 1553-7358
- Page Range / eLocation ID:
- e1009808
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1371/journal.pcbi.1009808
