Adaptive Efficient Coding of Correlated Acoustic Properties

Abstract

Natural sounds such as vocalizations often have covarying acoustic attributes, resulting in redundancy in neural coding. The efficient coding hypothesis proposes that sensory systems are able to detect such covariation and adapt to reduce redundancy, leading to more efficient neural coding. Recent psychoacoustic studies have shown the auditory system can rapidly adapt to efficiently encode two covarying dimensions as a single dimension, following passive exposure to sounds in which temporal and spectral attributes covaried in a correlated fashion. However, these studies observed a cost to this adaptation, which was a loss of sensitivity to the orthogonal dimension. Here we explore the neural basis of this psychophysical phenomenon by recording single-unit responses from the primary auditory cortex in awake ferrets exposed passively to stimuli with two correlated attributes, similar in stimulus design to the psychoacoustic experiments in humans. We found: (1) the signal-to-noise ratio of spike-rate coding of cortical responses driven by sounds with correlated attributes remained unchanged along the exposure dimension, but was reduced along the orthogonal dimension; (2) performance of a decoder trained with spike data to discriminate stimuli along the orthogonal dimension was equally reduced; (3) correlations between neurons tuned to the two covarying attributes decreased after exposure; and (4) these exposure effects still occurred if sounds were correlated along two acoustic dimensions, but varied randomly along a third dimension. These neurophysiological results are consistent with the efficient coding hypothesis and may help deepen our understanding of how the auditory system encodes and represents acoustic regularities and covariance.

An optimal-fitness framework for modeling perceptual compression

“…This model is corroborated by findings that the input-output curves of individual sensory neurons are optimally adapted to encode naturalistic stimulus intensity distributions (1). This model is further corroborated by findings that neuron populations in visual, auditory, and olfactory systems exhibit: information-maximizing features (such as reduction of redundancy between neurons) that manifest specifically during the processing of naturalistic stimuli (3)(4)(5)(6)(7), stimulus coding that is adapted to the distribution of naturalistic stimuli (8), and code plasticity when the distribution of their environment's stimuli changes (9,10). Also, MI maximization is an evolutionarily plausible compression strategy because it limits the surprise associated with an organism's action-driven state transitions, and thereby facilitates the organism's pursuit of highvalue states (11).…”

“…As illustrated in Fig 4A, in the E4 environments in which item values are drawn from N(1,1) and 𝑛𝑛 ∈[9,10], the AMR-maximizing compression strategy's pursuit of large rewards is fittest when fitness is based on AMR, while the BH compression strategy's pursuit of steady rewards is fittest when fitness is based on GMR. Additional insight can be gained from examining why the AMR-maximizing compression strategy fails to produce the BH compression strategy's steady rewards.…”

Temporal Coherence Shapes Cortical Responses to Speech Mixtures in a Ferret Cocktail Party

“…The other critical ingredient for segregation to occur is the notion of "binding", namely that highly correlated cells (within the female-or male-cluster) rapidly form excitatory inter-connections that mutually enhance their responses. The opposite happens between anti-or weakly-correlated cells which form mutually inhibitory connections that suppress the cells [27,38]. Thus, in the case of a mixture of two speakers, if a listener attends to one voice, e.g., the ferret attending to the female voice, all it needs to do is boost the responses to one distinctive attribute, e.g., the pitch or location (if they are separated).…”