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Neural oscillations are at the core of important computations in the mammalian brain. Interactions between oscillatory activities in different frequency bands, such as delta (1–4 Hz), theta (4–8 Hz) or gamma (>30 Hz), are a powerful mechanism for binding fundamentally distinct spatiotemporal scales of neural processing. Phase-amplitude coupling (PAC) is one such plausible and well-described interaction, but much is yet to be uncovered regarding how PAC dynamics contribute to sensory representations. In particular, although PAC appears to have a major role in audition, the characteristics of coupling profiles in sensory and integration (i.e. frontal) cortical areas remain obscure. Here, we address this question by studying PAC dynamics in the frontal-auditory field (FAF; an auditory area in the bat frontal cortex) and the auditory cortex (AC) of the bat Carollia perspicillata. By means of simultaneous electrophysiological recordings in frontal and auditory cortices examining local-field potentials (LFPs), we show that the amplitude of gamma-band activity couples with the phase of low-frequency LFPs in both structures. Our results demonstrate that the coupling in FAF occurs most prominently in delta/high-gamma frequencies (1-4/75-100 Hz), whereas in the AC the coupling is strongest in the delta-theta/low-gamma (2-8/25-55 Hz) range. We argue that distinct PAC profiles may represent different mechanisms for neuronal processing in frontal and auditory cortices, and might complement oscillatory interactions for sensory processing in the frontal-auditory cortex network.
Sound discrimination is essential in many species for communicating and foraging. Bats, for example, use sounds for echolocation and communication. In the bat auditory cortex there are neurons that process both sound categories, but how these neurons respond to acoustic transitions, that is, echolocation streams followed by a communication sound, remains unknown. Here, we show that the acoustic context, a leading sound sequence followed by a target sound, changes neuronal discriminability of echolocation versus communication calls in the cortex of awake bats of both sexes. Nonselective neurons that fire equally well to both echolocation and communication calls in the absence of context become category selective when leading context is present. On the contrary, neurons that prefer communication sounds in the absence of context turn into nonselective ones when context is added. The presence of context leads to an overall response suppression, but the strength of this suppression is stimulus specific. Suppression is strongest when context and target sounds belong to the same category, e.g.,echolocation followed by echolocation. A neuron model of stimulus-specific adaptation replicated our results in silico The model predicts selectivity to communication and echolocation sounds in the inputs arriving to the auditory cortex, as well as two forms of adaptation, presynaptic frequency-specific adaptation acting in cortical inputs and stimulus-unspecific postsynaptic adaptation. In addition, the model predicted that context effects can last up to 1.5 s after context offset and that synaptic inputs tuned to low-frequency sounds (communication signals) have the shortest decay constant of presynaptic adaptation.SIGNIFICANCE STATEMENT We studied cortical responses to isolated calls and call mixtures in awake bats and show that (1) two neuronal populations coexist in the bat cortex, including neurons that discriminate social from echolocation sounds well and neurons that are equally driven by these two ethologically different sound types; (2) acoustic context (i.e., other natural sounds preceding the target sound) affects natural sound selectivity in a manner that could not be predicted based on responses to isolated sounds; and (3) a computational model similar to those used for explaining stimulus-specific adaptation in rodents can account for the responses observed in the bat cortex to natural sounds. This model depends on segregated feedforward inputs, synaptic depression, and postsynaptic neuronal adaptation.