Dataset Information

Neural Correlates of Learning Pure Tones or Natural Sounds in the Auditory Cortex.

ABSTRACT: Associative learning of pure tones is known to cause tonotopic map expansion in the auditory cortex (ACx), but the function this plasticity sub-serves is unclear. We developed an automated training platform called the "Educage," which was used to train mice on a go/no-go auditory discrimination task to their perceptual limits, for difficult discriminations among pure tones or natural sounds. Spiking responses of excitatory and inhibitory parvalbumin (PV+) L2/3 neurons in mouse ACx revealed learning-induced overrepresentation of the learned frequencies, as expected from previous literature. The coordinated plasticity of excitatory and inhibitory neurons supports a role for PV+ neurons in homeostatic maintenance of excitation-inhibition balance within the circuit. Using a novel computational model to study auditory tuning curves, we show that overrepresentation of the learned tones does not necessarily improve discrimination performance of the network to these tones. In a separate set of experiments, we trained mice to discriminate among natural sounds. Perceptual learning of natural sounds induced "sparsening" and decorrelation of the neural response, consequently improving discrimination of these complex sounds. This signature of plasticity in A1 highlights its role in coding natural sounds.

SUBMITTER: Maor I

PROVIDER: S-EPMC6997498 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Neural Correlates of Learning Pure Tones or Natural Sounds in the Auditory Cortex.

Maor Ido I Shwartz-Ziv Ravid R Feigin Libi L Elyada Yishai Y Sompolinsky Haim H Mizrahi Adi A

Frontiers in neural circuits 20200128

Associative learning of pure tones is known to cause tonotopic map expansion in the auditory cortex (ACx), but the function this plasticity sub-serves is unclear. We developed an automated training platform called the "Educage," which was used to train mice on a go/no-go auditory discrimination task to their perceptual limits, for difficult discriminations among pure tones or natural sounds. Spiking responses of excitatory and inhibitory parvalbumin (PV<sup>+</sup>) L2/3 neurons in mouse ACx rev ...[more]

PMID: 32047424

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Project description:We investigate how the neural processing in auditory cortex is shaped by the statistics of natural sounds. Hypothesising that auditory cortex (A1) represents the structural primitives out of which sounds are composed, we employ a statistical model to extract such components. The input to the model are cochleagrams which approximate the non-linear transformations a sound undergoes from the outer ear, through the cochlea to the auditory nerve. Cochleagram components do not superimpose linearly, but rather according to a rule which can be approximated using the max function. This is a consequence of the compression inherent in the cochleagram and the sparsity of natural sounds. Furthermore, cochleagrams do not have negative values. Cochleagrams are therefore not matched well by the assumptions of standard linear approaches such as sparse coding or ICA. We therefore consider a new encoding approach for natural sounds, which combines a model of early auditory processing with maximal causes analysis (MCA), a sparse coding model which captures both the non-linear combination rule and non-negativity of the data. An efficient truncated EM algorithm is used to fit the MCA model to cochleagram data. We characterize the generative fields (GFs) inferred by MCA with respect to in vivo neural responses in A1 by applying reverse correlation to estimate spectro-temporal receptive fields (STRFs) implied by the learned GFs. Despite the GFs being non-negative, the STRF estimates are found to contain both positive and negative subfields, where the negative subfields can be attributed to explaining away effects as captured by the applied inference method. A direct comparison with ferret A1 shows many similar forms, and the spectral and temporal modulation tuning of both ferret and model STRFs show similar ranges over the population. In summary, our model represents an alternative to linear approaches for biological auditory encoding while it captures salient data properties and links inhibitory subfields to explaining away effects.

Project description:Behaviorally-relevant sounds such as conspecific vocalizations are often available for only a brief amount of time; thus, goal-directed behavior frequently depends on auditory short-term memory (STM). Despite its ecological significance, the neural processes underlying auditory STM remain poorly understood. To investigate the role of the auditory cortex in STM, single- and multi-unit activity was recorded from the primary auditory cortex (A1) of two monkeys performing an auditory STM task using simple and complex sounds. Each trial consisted of a sample and test stimulus separated by a 5-s retention interval. A brief wait period followed the test stimulus, after which subjects pressed a button if the sounds were identical (match trials) or withheld button presses if they were different (non-match trials). A number of units exhibited significant changes in firing rate for portions of the retention interval, although these changes were rarely sustained. Instead, they were most frequently observed during the early and late portions of the retention interval, with inhibition being observed more frequently than excitation. At the population level, responses elicited on match trials were briefly suppressed early in the sound period relative to non-match trials. However, during the latter portion of the sound, firing rates increased significantly for match trials and remained elevated throughout the wait period. Related patterns of activity were observed in prior experiments from our lab in the dorsal temporal pole (dTP) and prefrontal cortex (PFC) of the same animals. The data suggest that early match suppression occurs in both A1 and the dTP, whereas later match enhancement occurs first in the PFC, followed by A1 and later in dTP. Because match enhancement occurs first in the PFC, we speculate that enhancement observed in A1 and dTP may reflect top-down feedback. Overall, our findings suggest that A1 forms part of the larger neural system recruited during auditory STM.

Dataset Information

Neural Correlates of Learning Pure Tones or Natural Sounds in the Auditory Cortex.

Publications

Neural Correlates of Learning Pure Tones or Natural Sounds in the Auditory Cortex.

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