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Animals navigate the auditory world by recognizing complex sounds, from the rustle of a predator to the call of a potential mate. This ability depends in part on the octopus cells of the auditory brainstem, which respond to multiple frequencies that change over time, as occurs in natural stimuli. Unlike the average neuron, which integrates inputs over time on the order of tens of milliseconds, octopus cells must detect momentary coincidence of excitatory inputs from the cochlea during an ongoing sound on both the millisecond and submillisecond time scale. Here, we show that octopus cells receive inhibitory inputs on their dendrites that enhance opportunities for coincidence detection in the cell body, thereby allowing for responses both to rapid onsets at the beginning of a sound and to frequency modulations during the sound. This mechanism is crucial for the fundamental process of integrating the synchronized frequencies of natural auditory signals over time., Competing Interests: Declaration of Interests The authors declare no competing interests.

The central nucleus of the inferior colliculus (ICC) integrates information about different features of sound and then distributes this information to thalamocortical circuits. However, the lack of clear definitions of circuit elements in the ICC has limited our understanding of the nature of these circuit transformations. Here, we combine virus-based genetic access with electrophysiological and optogenetic approaches to identify a large family of excitatory, cholecystokinin-expressing thalamic projection neurons in the ICC of the Mongolian gerbil. We show that these neurons form a distinct cell type, displaying uniform morphology and intrinsic firing features, and provide powerful, spatially restricted excitation exclusively to the ventral auditory thalamus. In vivo, these neurons consistently exhibit V-shaped receptive field properties but strikingly diverse temporal responses to sound. Our results indicate that temporal response diversity is maintained within this population of otherwise uniform cells in the ICC and then relayed to cortex through spatially restricted thalamic subdomains., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Central amygdala (CeA) neurons that produce corticotropin-releasing factor (CRF) regulate anxiety and fear learning. These CeA CRF neurons release GABA and several neuropeptides predicted to play important yet opposing roles in these behaviors. We dissected the relative roles of GABA, CRF, dynorphin, and neurotensin in CeA CRF neurons in anxiety and fear learning by disrupting their expression using RNAi in male rats. GABA, but not CRF, dynorphin, or neurotensin, regulates baseline anxiety-like behavior. In contrast, chemogenetic stimulation of CeA CRF neurons evokes anxiety-like behavior dependent on CRF and dynorphin, but not neurotensin. Finally, knockdown of CRF and dynorphin impairs fear learning, whereas knockdown of neurotensin enhances it. Our results demonstrate distinct behavioral roles for GABA, CRF, dynorphin, and neurotensin in a subpopulation of CeA neurons. These results highlight the importance of considering the repertoire of signaling molecules released from a given neuronal population when studying the circuit basis of behavior., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Reliable representation of the spectrotemporal features of an acoustic stimulus is critical for sound recognition. However, if all neurons respond with identical firing to the same stimulus, redundancy in the activity patterns would reduce the information capacity of the population. We thus investigated spike reliability and temporal fluctuation coding in an ensemble of neurons recorded in vitro from the avian auditory brain stem. Sequential patch-clamp recordings were made from neurons of the cochlear nucleus angularis while injecting identical filtered Gaussian white noise currents, simulating synaptic drive. The spiking activity in neurons receiving these identically fluctuating stimuli was highly correlated, measured pairwise across neurons and as a pseudo-population. Two distinct uncorrelated noise stimuli could be discriminated using the temporal patterning, but not firing rate, of the spike trains in the neural ensemble, with best discrimination using information at time scales of 5-20 ms. Despite high cross-correlation values, the spike patterns observed in individual neurons were idiosyncratic, with notable heterogeneity across neurons. To investigate how temporal information is being encoded, we used optimal linear reconstruction to produce an estimate of the original current stimulus from the spike trains. Ensembles of trains sampled across the neural population could be used to predict >50% of the stimulus variation using optimal linear decoding, compared with ∼20% using the same number of spike trains recorded from single neurons. We conclude that heterogeneity in the intrinsic biophysical properties of cochlear nucleus neurons reduces firing pattern redundancy while enhancing representation of temporal information., (Copyright © 2014 the American Physiological Society.)

The intrinsic properties of tonically firing neurons in the cochlear nucleus contribute to representing average sound intensity by favoring synaptic integration across auditory nerve inputs, reducing phase locking to fine temporal acoustic structure and enhancing envelope locking. To determine whether tonically firing neurons of the avian cochlear nucleus angularis (NA) resemble ideal integrators, we investigated their firing responses to noisy current injections during whole cell patch-clamp recordings in brain slices. One subclass of neurons (36% of tonically firing neurons, mainly subtype tonic III) showed no significant changes in firing rate with noise fluctuations, acting like pure integrators. In contrast, many tonically firing neurons (>60%, mainly subtype tonic I or II) showed a robust sensitivity to noisy current fluctuations, increasing their firing rates with increased fluctuation amplitudes. For noise-sensitive tonic neurons, the firing rate vs. average current curves with noise had larger maximal firing rates, lower gains, and wider dynamic ranges compared with FI curves for current steps without noise. All NA neurons showed fluctuation-driven patterning of spikes with a high degree of temporal reliability and millisecond spike time precision. Single-spiking neurons in NA also responded to noisy currents with higher firing rates and reliable spike trains, although less precisely than nucleus magnocellularis neurons. Thus some NA neurons function as integrators by encoding average input levels over wide dynamic ranges regardless of current fluctuations, others detect the degree of coherence in the inputs, and most encode the temporal patterns contained in their inputs with a high degree of precision.