Representation of communication sounds in the inferior colliculus of the guinea pig

The spectrotemporal discharge patterns of the neuronal population were clearly related to the spectrotemporal acoustic patterns of vocalization sounds.This study provides evidence for encoding of the spoctrotemporal acoustic pattern of vocalization sounds in a spcific and distributed way by the firing patterns of a population of IC units

Software for the Analysis of Species-Specific Vocalizations

Vocalization calls are behaviorally relevant complex sounds that typically contain several harmonics and show frequency and amplitude modulation. In this paper, an introduction to a software tool for the analysis of species-specific vocalizations is presented. The algorithm automatically or under user supervision detects time-varying amplitude and frequency parameters, which can serve for the statistical analysis of calls or as the substrate for the manipulation and synthesis of artificial calls. The described program and its results will be used in studying the representation of complex sounds in the central nervous system

Acoustically Enriched Environment during the Critical Period of Postnatal Development Positively Modulates Gap Detection and Frequency Discrimination Abilities in Adult Rats

Throughout life, sensory systems adapt to the sensory environment to provide optimal responses to relevant tasks. In the case of a developing system, sensory inputs induce changes that are permanent and detectable up to adulthood. Previously, we have shown that rearing rat pups in a complex acoustic environment (spectrally and temporally modulated sound) from postnatal day 14 (P14) to P28 permanently improves the response characteristics of neurons in the inferior colliculus and auditory cortex, influencing tonotopical arrangement, response thresholds and strength, and frequency selectivity, along with stochasticity and the reproducibility of neuronal spiking patterns. In this study, we used a set of behavioral tests based on a recording of the acoustic startle response (ASR) and its prepulse inhibition (PPI), with the aim to extend the evidence of the persistent beneficial effects of the developmental acoustical enrichment. The enriched animals were generally not more sensitive to startling sounds, and also, their PPI of ASR, induced by noise or pure tone pulses, was comparable to the controls. They did, however, exhibit a more pronounced PPI when the prepulse stimulus was represented either by a change in the frequency of a background tone or by a silent gap in background noise. The differences in the PPI of ASR between the enriched and control animals were significant at lower (55 dB SPL), but not at higher (65-75 dB SPL), intensities of background sound. Thus, rearing pups in the acoustically enriched environment led to an improvement of the frequency resolution and gap detection ability under more difficult testing conditions, i.e., with a worsened stimulus clarity. We confirmed, using behavioral tests, that an acoustically enriched environment during the critical period of development influences the frequency and temporal processing in the auditory system, and these changes persist until adulthood

Cortical Representation of Species-Specific Vocalizations in Guinea Pig

<div><p>We investigated the representation of four typical guinea pig vocalizations in the auditory cortex (AI) in anesthetized guinea pigs with the aim to compare cortical data to the data already published for identical calls in subcortical structures - the inferior colliculus (IC) and medial geniculate body (MGB). Like the subcortical neurons also cortical neurons typically responded to many calls with a time-locked response to one or more temporal elements of the calls. The neuronal response patterns in the AI correlated well with the sound temporal envelope of chirp (an isolated short phrase), but correlated less well in the case of chutter and whistle (longer calls) or purr (a call with a fast repetition rate of phrases). Neuronal rate vs. characteristic frequency profiles provided only a coarse representation of the calls’ frequency spectra. A comparison between the activity in the AI and those of subcortical structures showed a different transformation of the neuronal response patterns from the IC to the AI for individual calls: i) while the temporal representation of chirp remained unchanged, the representations of whistle and chutter were transformed at the thalamic level and the response to purr at the cortical level; ii) for the wideband calls (whistle, chirp) the rate representation of the call spectra was preserved in the AI and MGB at the level present in the IC, while in the case of low-frequency calls (chutter, purr), the representation was less precise in the AI and MGB than in the IC; iii) the difference in the response strength to natural and time-reversed whistle was found to be smaller in the AI than in the IC or MGB.</p></div

Comparison of subcortical nuclei (IC, MGB) and the auditory cortex.

<p>The correlation coefficients between the sound envelope and the averaged PSTH (A) and the correlation coefficients between the sound frequency spectrum and rate vs. CF profile (C) are compared in the inferior colliculus (IC, open), medial geniculate body (MGB, blue) and auditory cortex (AI, red) for individual call. Panel (B) shows a schematic drawing of a part of the ascending auditory pathway. IC data based on 153 neurons are taken from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065432#pone.0065432-uta1" target="_blank">[2]</a>; MGB data calculated from 209 neurons are taken from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065432#pone.0065432-uta2" target="_blank">[18]</a>. The bootstrap method was used to determine whether the values of the correlation coefficients in individual nuclei were statistically different (P<0.01). The blue stars indicate cases of tecto-thalamic transformation of the neuronal response in which the IC data were significantly different from the MGB and AI data, while the difference between the MGB and AI was not significant. The red star indicates a case of thalamo-cortical transformation of the neuronal response in which the AI data were significantly different from MGB and IC data, while the difference between the MGB and IC was not significant.</p

Comparisons of the rate-CF profiles (n = 502, top) and call short-term spectra (bottom) for three consecutive parts of whistle (A–C – the appropriate time interval is indicated above every rate-CF profile), for purr (D – data calculated over the first phase containing four elementary phrases), for chirp (E) and for chutter (F – calculated over the first phrase of the call).

<p>Comparisons of the rate-CF profiles (n = 502, top) and call short-term spectra (bottom) for three consecutive parts of whistle (A–C – the appropriate time interval is indicated above every rate-CF profile), for purr (D – data calculated over the first phase containing four elementary phrases), for chirp (E) and for chutter (F – calculated over the first phrase of the call).</p