bioRxivNeurosciencePreprint
Listening with your heart: The heartbeat shapes auditory object formation by suppressing the early neural response to sound
John P. VeilletteiD, Aditi Joshi, Ying LiiD, Howard C. NusbaumiD
Abstract
Interoceptive sensations, arising from the body's visceral organs such as the heart, are known to impact exteroceptive sensory perception. The classical explanation for heart-to-brain influence, the Baroreceptor Hypothesis, posits that baroreceptors firing during the systolic blood pressure peaks that follow each heartbeat suppress the magnitude of neural responses to exteroceptive sensations. More recent work, however, has demonstrated qualitative (rather than merely magnitude) differences in perception as a function of the cardiac cycle; since it is not obvious how the Baroreceptor Hypothesis could explain these findings, even in principle, they have often been characterized as incompatible. We propose baroreceptor-related suppression of early sensorineural responses need not manifest simply as suppression of corresponding conscious percepts. In a validated computational model of auditory cortex that segregates an ambiguous tone sequence into either one or two auditory objects or "streams," we found suppression of the neural response to one tone type increases the likelihood that tone is parsed into a distinct stream. We subsequently verified this prediction empirically: when presenting such ambiguous sequences to human participants in a manner such that one tone type only occurs during cardiac systole, the initial neural response to that tone -- indexed by the electroencephalographic (EEG) frequency-following response (FFR) -- is indeed suppressed, while participants report hearing the sequence as two separate sounds streams more frequently. Thus, suppression of early sensorineural responses can be sufficient to explain qualitative, not just magnitude, differences in perception when considered in the context of larger neural circuits.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 0
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